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ORCIDSaikat Chatterjee
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2020 – today
- 2024
[j43]Anubhab Ghosh
, Mohamed Abdalmoaty, Saikat Chatterjee, Håkan Hjalmarsson:
DeepBayes - An estimator for parameter estimation in stochastic nonlinear dynamical models. Autom. 159: 111327 (2024)- [j42]Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee:
DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup. IEEE Trans. Signal Process. 72: 1824-1838 (2024) - [c95]Xinyu Liang, Fredrik Cumlin, Victor Ungureanu, Chandan K. A. Reddy, Christian Schüldt, Saikat Chatterjee:
DeePMOS-$\mathcal{B}$: Deep Posterior Mean-Opinion-Score Using Beta Distribution. EUSIPCO 2024: 416-420 - [c94]Sandipan Das, Bengt Boberg, Maurice F. Fallon, Saikat Chatterjee:
IMU-based Online Multi-lidar Calibration. IV 2024: 3227-3234 - [i61]Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee:
Data-driven Bayesian State Estimation with Compressed Measurement of Model-free Process using Semi-supervised Learning. CoRR abs/2407.07368 (2024) - [i60]Nir Shlezinger, Guy Revach, Anubhab Ghosh, Saikat Chatterjee, Shuo Tang, Tales Imbiriba, Jindrich Duník, Ondrej Straka, Pau Closas, Yonina C. Eldar:
AI-Aided Kalman Filters. CoRR abs/2410.12289 (2024) - 2023
- [j41]Saikat Chatterjee, Praphulla Koushik:
Extension of Topological Groupoids and Hurewicz Morphisms. Appl. Categorical Struct. 31(5): 33 (2023) - [j40]Sandipan Das, Ludvig af Klinteberg, Maurice F. Fallon, Saikat Chatterjee:
Observability-Aware Online Multi-Lidar Extrinsic Calibration. IEEE Robotics Autom. Lett. 8(5): 2860-2867 (2023) - [c93]Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee:
Latent-Based Neural Net for Non-Intrusive Speech Quality Assessment. EUSIPCO 2023: 226-230 - [c92]Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee:
DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Bayesian Setup. EUSIPCO 2023: 870-874 - [c91]Antoine Honoré, Anubhab Ghosh, Saikat Chatterjee:
Compressed Sensing of Generative Sparse-Latent (GSL) Signals. EUSIPCO 2023: 1918-1922 - [c90]Xinyu Liang, Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee:
DeePMOS: Deep Posterior Mean-Opinion-Score of Speech. INTERSPEECH 2023: 526-530 - [c89]Sandipan Das, Navid Mahabadi, Maurice F. Fallon, Saikat Chatterjee:
M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance. IV 2023: 1-7 - [i59]Ritumbra Manuvie, Saikat Chatterjee:
Automated Sentiment and Hate Speech Analysis of Facebook Data by Employing Multilingual Transformer Models. CoRR abs/2301.13668 (2023) - [i58]Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee:
DANSE: Data-driven Non-linear State Estimation of Model-free Process in Unsupervised Learning Setup. CoRR abs/2306.03897 (2023) - [i57]Ritumbra Manuvie, Saikat Chatterjee:
Identifying and analysing toxic actors and communities on Facebook by employing network analysis. CoRR abs/2309.07608 (2023) - [i56]Antoine Honoré, Anubhab Ghosh, Saikat Chatterjee:
Compressed Sensing of Generative Sparse-latent (GSL) Signals. CoRR abs/2310.15119 (2023) - 2022
- [j39]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Decentralized learning of randomization-based neural networks with centralized equivalence. Appl. Soft Comput. 115: 108030 (2022) - [j38]Simei Yang, Debjyoti Bhattacharjee, Vinay B. Y. Kumar, Saikat Chatterjee, Sayandip De, Peter Debacker, Diederik Verkest, Arindam Mallik, Francky Catthoor:
AERO: Design Space Exploration Framework for Resource-Constrained CNN Mapping on Tile-Based Accelerators. IEEE J. Emerg. Sel. Topics Circuits Syst. 12(2): 508-521 (2022) - [j37]Fatemeh Arian, Mehdi Amini, Shayan Mostafaei, Kiara Rezaei-Kalantari, Atlas Haddadi Avval, Zahra Shahbazi, Kianosh Kasani, Ahmad Bitarafan-rajabi, Saikat Chatterjee, Mehrdad Oveisi, Isaac Shiri, Habib Zaidi:
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms. J. Digit. Imaging 35(6): 1708-1718 (2022) - [c88]Anubhab Ghosh, Aleix Espuña Fontcuberta, Mohamed Rasheed-Hilmy Abdalmoaty, Saikat Chatterjee:
Time-varying Normalizing Flow for Generative Modeling of Dynamical Signals. EUSIPCO 2022: 1492-1496 - [c87]Pol Grau Jurado, Xinyue Liang, Saikat Chatterjee:
Deterministic Transform Based Weight Matrices for Neural Networks. ICASSP 2022: 4528-4532 - [c86]Sandipan Das, Navid Mahabadi, Addi Djikic, Cesar Nassir, Saikat Chatterjee, Maurice F. Fallon:
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors. ICRA 2022: 919-925 - [c85]Sandipan Das, Alireza M. Javid, Prakash Borpatra Gohain, Yonina C. Eldar, Saikat Chatterjee:
Neural Greedy Pursuit for Feature Selection. IJCNN 2022: 1-7 - [i55]Anubhab Ghosh, Mohamed Rasheed Abdalmoaty, Saikat Chatterjee, Håkan Hjalmarsson:
DeepBayes - an estimator for parameter estimation in stochastic nonlinear dynamical models. CoRR abs/2205.02264 (2022) - [i54]Sandipan Das, Navid Mahabadi, Saikat Chatterjee, Maurice F. Fallon:
Multi-modal curb detection and filtering. CoRR abs/2205.07096 (2022) - [i53]Sandipan Das, Navid Mahabadi, Addi Djikic, Cesar Nassir, Saikat Chatterjee, Maurice F. Fallon:
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors. CoRR abs/2205.07098 (2022) - [i52]Sandipan Das, Alireza M. Javid, Prakash Borpatra Gohain, Yonina C. Eldar, Saikat Chatterjee:
Neural Greedy Pursuit for Feature Selection. CoRR abs/2207.09390 (2022) - [i51]Sandipan Das, Navid Mahabadi, Maurice F. Fallon, Saikat Chatterjee:
M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance. CoRR abs/2210.01154 (2022) - [i50]Sandipan Das, Ludvig af Klinteberg, Maurice F. Fallon, Saikat Chatterjee:
Observability-aware online multi-lidar extrinsic calibration. CoRR abs/2212.09579 (2022) - 2021
- [c84]Pol Grau Jurado, Xinyue Liang, Alireza M. Javid, Saikat Chatterjee:
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network. EUSIPCO 2021: 1366-1370 - [c83]Helmer Nylén, Saikat Chatterjee, Sten Ternström:
Detecting Signal Corruptions in Voice Recordings For Speech Therapy. ICASSP 2021: 386-390 - [c82]Xinyue Liang, Mikael Skoglund, Saikat Chatterjee:
Feature Reuse for a Randomization Based Neural Network. ICASSP 2021: 2805-2809 - [c81]Alireza M. Javid, Sandipan Das, Mikael Skoglund, Saikat Chatterjee:
A ReLU Dense Layer to Improve the Performance of Neural Networks. ICASSP 2021: 2810-2814 - [c80]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Asynchronous Decentralized Learning of Randomization-Based Neural Networks. IJCNN 2021: 1-8 - [i49]Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee:
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows. CoRR abs/2102.07284 (2021) - [i48]Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee:
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability. CoRR abs/2107.00730 (2021) - [i47]Pol Grau Jurado, Xinyue Liang, Alireza M. Javid, Saikat Chatterjee:
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network. CoRR abs/2110.03515 (2021) - 2020
- [j36]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-dimensional neural feature design for layer-wise reduction of training cost. EURASIP J. Adv. Signal Process. 2020(1): 40 (2020) - [j35]Sajad Mehrizi, Saikat Chatterjee, Symeon Chatzinotas, Björn E. Ottersten:
Online Spatiotemporal Popularity Learning via Variational Bayes for Cooperative Caching. IEEE Trans. Commun. 68(11): 7068-7082 (2020) - [c79]Zhijing Li, YangYang Lan, Saikat Chatterjee, Pargorn Puttapirat, Xiangrong Zhang, Chen Li:
Dual sentence representation model integrating prior knowledge for bio-text-mining. BIBM 2020: 2409-2416 - [c78]Dong Liu, Antoine Honoré, Saikat Chatterjee, Lars K. Rasmussen:
Powering Hidden Markov Model by Neural Network Based Generative Models. ECAI 2020: 1324-1331 - [c77]Filip Wen-Fwu Tsai, Alireza M. Javid, Saikat Chatterjee:
Design of a Non-negative Neural Network to Improve on NMF. EUSIPCO 2020: 461-465 - [c76]Alireza M. Javid, Xinyue Liang, Mikael Skoglund, Saikat Chatterjee:
Adaptive Learning without Forgetting via Low-Complexity Convex Networks. EUSIPCO 2020: 1623-1627 - [c75]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Learning without Forgetting for Decentralized Neural Nets with Low Communication Overhead. EUSIPCO 2020: 2185-2189 - [c74]Antoine Honoré, Dong Liu, David Forsberg, Karen Coste, Eric Herlenius, Saikat Chatterjee, Mikael Skoglund:
Hidden Markov Models for Sepsis Detection in Preterm Infants. ICASSP 2020: 1130-1134 - [c73]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Asynchrounous Decentralized Learning of a Neural Network. ICASSP 2020: 3947-3951 - [c72]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance. ICASSP 2020: 4237-4241 - [c71]Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg:
Recursive Prediction of Graph Signals With Incoming Nodes. ICASSP 2020: 5565-5569 - [c70]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Gaussian Processes Over Graphs. ICASSP 2020: 5640-5644 - [c69]Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen:
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning. IJCNN 2020: 1-10 - [c68]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning. IJCNN 2020: 1-8 - [c67]Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee:
Robust Classification Using Hidden Markov Models and Mixtures of Normalizing Flows. MLSP 2020: 1-6 - [i46]Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee:
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance. CoRR abs/2003.13058 (2020) - [i45]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Asynchronous Decentralized Learning of a Neural Network. CoRR abs/2004.05082 (2020) - [i44]Alireza M. Javid, Xinyue Liang, Arun Venkitaraman, Saikat Chatterjee:
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University. CoRR abs/2005.05060 (2020) - [i43]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning. CoRR abs/2009.13982 (2020) - [i42]Alireza M. Javid, Sandipan Das, Mikael Skoglund, Saikat Chatterjee:
A ReLU Dense Layer to Improve the Performance of Neural Networks. CoRR abs/2010.13572 (2020) - [i41]Sandipan Das, Prakash B. Gohain, Alireza M. Javid, Yonina C. Eldar, Saikat Chatterjee:
Statistical model-based evaluation of neural networks. CoRR abs/2011.09015 (2020)
2010 – 2019
- 2019
- [j34]Ahmed Zaki, Partha P. Mitra, Lars K. Rasmussen, Saikat Chatterjee:
Estimate exchange over network is good for distributed hard thresholding pursuit. Signal Process. 156: 1-11 (2019) - [j33]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
On Hilbert transform, analytic signal, and modulation analysis for signals over graphs. Signal Process. 156: 106-115 (2019) - [j32]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph. IEEE Trans. Signal Inf. Process. over Networks 5(4): 698-710 (2019) - [c66]Mostafa Sadeghi, Fateme Ghayem, Massoud Babaie-Zadeh, Saikat Chatterjee, Mikael Skoglund, Christian Jutten:
LOSoft: ℓ0 Minimization via Soft Thresholding. EUSIPCO 2019: 1-5 - [c65]Ahmed Zaki, Saikat Chatterjee:
Convex Optimization Based Sparse Learning Over Networks. EUSIPCO 2019: 1-5 - [c64]Dong Liu, Nima N. Moghadam, Lars K. Rasmussen, Jinliang Huang, Saikat Chatterjee:
α Belief Propagation as Fully Factorized Approximation. GlobalSIP 2019: 1-5 - [c63]Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen:
Entropy-regularized Optimal Transport Generative Models. ICASSP 2019: 3532-3536 - [c62]Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee:
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. ICASSP 2019: 5426-5430 - [i40]Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi, Shumpei Kikuta, Partha P. Mitra, Mikael Skoglund:
SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design. CoRR abs/1905.07111 (2019) - [i39]Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen:
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning. CoRR abs/1907.13432 (2019) - [i38]Dong Liu, Nima N. Moghadam, Lars K. Rasmussen, Jinliang Huang, Saikat Chatterjee:
α Belief Propagation as Fully Factorized Approximation. CoRR abs/1908.08906 (2019) - [i37]Dong Liu, Antoine Honoré, Saikat Chatterjee, Lars K. Rasmussen:
Powering Hidden Markov Model by Neural Network based Generative Models. CoRR abs/1910.05744 (2019) - [i36]Antoine Honoré, Dong Liu, David Forsberg, Karen Coste, Eric Herlenius, Saikat Chatterjee, Mikael Skoglund:
Hidden Markov Models for sepsis detection in preterm infants. CoRR abs/1910.13904 (2019) - [i35]Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg:
Recursive Prediction of Graph Signals with Incoming Nodes. CoRR abs/1911.11542 (2019) - 2018
- [j31]Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars Kildehoj Rasmussen:
Greedy Sparse Learning Over Network. IEEE Trans. Signal Inf. Process. over Networks 4(3): 424-435 (2018) - [j30]Fateme Ghayem, Mostafa Sadeghi, Massoud Babaie-Zadeh, Saikat Chatterjee, Mikael Skoglund, Christian Jutten:
Sparse Signal Recovery Using Iterative Proximal Projection. IEEE Trans. Signal Process. 66(4): 879-894 (2018) - [c61]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Extreme Learning Machine for Graph Signal Processing. EUSIPCO 2018: 136-140 - [c60]Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee:
Distributed Large Neural Network with Centralized Equivalence. ICASSP 2018: 2976-2980 - [c59]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Multi-Kernel Regression for Graph Signal Processing. ICASSP 2018: 4644-4648 - [c58]Alireza M. Javid, Saikat Chatterjee, Mikael Skoglund:
Mutual Information Preserving Analysis of a Single Layer Feedforward Network. ISWCS 2018: 1-5 - [i34]Arun Venkitaraman, Alireza M. Javid, Saikat Chatterjee:
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network. CoRR abs/1803.04186 (2018) - [i33]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Extreme Learning Machine for Graph Signal Processing. CoRR abs/1803.04193 (2018) - [i32]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Multi-kernel Regression For Graph Signal Processing. CoRR abs/1803.04196 (2018) - [i31]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Gaussian Processes Over Graphs. CoRR abs/1803.05776 (2018) - [i30]Ahmed Zaki, Saikat Chatterjee, Partha P. Mitra, Lars K. Rasmussen:
Locally Convex Sparse Learning over Networks. CoRR abs/1804.00130 (2018) - [i29]Arun Venkitaraman, Hermina Petric Maretic, Saikat Chatterjee, Pascal Frossard:
Supervised Linear Regression for Graph Learning from Graph Signals. CoRR abs/1811.01586 (2018) - [i28]Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee:
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. CoRR abs/1811.02314 (2018) - [i27]Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen:
Entropy-regularized Optimal Transport Generative Models. CoRR abs/1811.06763 (2018) - 2017
- [j29]Ahmed Zaki, Saikat Chatterjee, Lars K. Rasmussen:
Generalized fusion algorithm for compressive sampling reconstruction and RIP-based analysis. Signal Process. 139: 36-48 (2017) - [c57]Martin Sundin, Arun Venkitaraman, Magnus Jansson, Saikat Chatterjee:
A connectedness constraint for learning sparse graphs. EUSIPCO 2017: 151-155 - [c56]Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars K. Rasmussen:
Distributed greedy sparse learning over doubly stochastic networks. EUSIPCO 2017: 361-364 - [i26]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Kernel Regression for Signals over Graphs. CoRR abs/1706.02191 (2017) - [i25]Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi, Partha P. Mitra, Mikael Skoglund:
Progressive Learning for Systematic Design of Large Neural Networks. CoRR abs/1710.08177 (2017) - [i24]Antoine Honoré, Veronica Siljehav, Saikat Chatterjee, Eric Herlenius:
Large Neural Network Based Detection of Apnea, Bradycardia and Desaturation Events. CoRR abs/1711.06484 (2017) - 2016
- [j28]Kezhi Li, Martin Sundin, Cristian R. Rojas, Saikat Chatterjee, Magnus Jansson:
Alternating strategies with internal ADMM for low-rank matrix reconstruction. Signal Process. 121: 153-159 (2016) - [j27]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee:
Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing. IEEE Trans. Inf. Theory 62(4): 2100-2124 (2016) - [j26]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Design and Analysis of a Greedy Pursuit for Distributed Compressed Sensing. IEEE Trans. Signal Process. 64(11): 2803-2818 (2016) - [j25]Martin Sundin, Cristian R. Rojas, Magnus Jansson, Saikat Chatterjee:
Relevance Singular Vector Machine for Low-Rank Matrix Reconstruction. IEEE Trans. Signal Process. 64(20): 5327-5339 (2016) - [c55]Martin Sundin, Saikat Chatterjee, Magnus Jansson:
Bayesian Cramer-Rao bounds for factorized model based low rank matrix reconstruction. EUSIPCO 2016: 1227-1231 - [c54]Gaurav Fotedar, Aditya Gaonkar P., Saikat Chatterjee, Prasanta Kumar Ghosh:
Automatic Recognition of Social Roles Using Long Term Role Transitions in Small Group Interactions. INTERSPEECH 2016: 2065-2069 - [i23]Arun Venkitaraman, Saikat Chatterjee, Peter Händel:
Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing. CoRR abs/1611.05269 (2016) - 2015
- [c53]Marten Vohrmann, Saikat Chatterjee, Sven Lütkemeier, Thorsten Jungeblut, Mario Porrmann, Ulrich Rückert:
A 65 nm standard cell library for ultra low-power applications. ECCTD 2015: 1-4 - [c52]Arun Venkitaraman, Saikat Chatterjee, Peter Handel:
Graph linear prediction results in smaller error than standard linear prediction. EUSIPCO 2015: 220-224 - [c51]Adria Casamitjana, Martin Sundin, Prasanta Kumar Ghosh, Saikat Chatterjee:
Bayesian learning for time-varying linear prediction of speech. EUSIPCO 2015: 325-329 - [c50]Ahmed Zaki, Saikat Chatterjee, Lars K. Rasmussen:
Universal algorithm for compressive sampling. EUSIPCO 2015: 689-693 - [c49]Martin Sundin, Saikat Chatterjee, Magnus Jansson:
Bayesian learning for robust principal component analysis. EUSIPCO 2015: 2361-2365 - [c48]Martin Sundin, Saikat Chatterjee, Magnus Jansson:
Greedy minimization of l1-norm with high empirical success. ICASSP 2015: 3816-3820 - [i22]Martin Sundin, Cristian R. Rojas, Magnus Jansson, Saikat Chatterjee:
Bayesian Learning for Low-Rank matrix reconstruction. CoRR abs/1501.05740 (2015) - 2014
- [j24]Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Mikko Vehkaperä, Mikael Skoglund, Lars K. Rasmussen, Erik Aurell, Jukka Corander:
SEK: sparsity exploiting k-mer-based estimation of bacterial community composition. Bioinform. 30(17): 2423-2431 (2014) - [j23]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Methods for Distributed Compressed Sensing. J. Sens. Actuator Networks 3(1): 1-25 (2014) - [j22]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing. Signal Process. 97: 146-151 (2014) - [j21]Zhanyu Ma, Saikat Chatterjee, W. Bastiaan Kleijn, Jun Guo:
Dirichlet mixture modeling to estimate an empirical lower bound for LSF quantization. Signal Process. 104: 291-295 (2014) - [j20]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Distributed greedy pursuit algorithms. Signal Process. 105: 298-315 (2014) - [j19]Dave Zachariah, Nafiseh Shariati, Mats Bengtsson, Magnus Jansson, Saikat Chatterjee:
Estimation for the Linear Model With Uncertain Covariance Matrices. IEEE Trans. Signal Process. 62(6): 1525-1535 (2014) - [j18]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
A Committee Machine Approach for Compressed Sensing Signal Reconstruction. IEEE Trans. Signal Process. 62(7): 1705-1717 (2014) - [j17]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Joint Source-Channel Vector Quantization for Compressed Sensing. IEEE Trans. Signal Process. 62(14): 3667-3681 (2014) - [c47]Kezhi Li, Cristian R. Rojas, Saikat Chatterjee, Håkan Hjalmarsson:
Piecewise Toeplitz matrices-based sensing for rank minimization. EUSIPCO 2014: 1836-1840 - [c46]Martin Sundin, Saikat Chatterjee, Magnus Jansson:
Combined modeling of sparse and dense noise improves Bayesian RVM. EUSIPCO 2014: 1841-1845 - [c45]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Distributed quantization for compressed sensing. ICASSP 2014: 6439-6443 - [c44]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee:
Analysis of regularized LS reconstruction and random matrix ensembles in compressed sensing. ISIT 2014: 3185-3189 - [c43]Prateek Basavapur Swamy, Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Reduced Look Ahead Orthogonal Matching Pursuit. NCC 2014: 1-6 - [c42]Christos Koniaris, Saikat Chatterjee:
A sparsity based preprocessing for noise robust speech recognition. SLT 2014: 513-518 - [i21]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
DIPP - Distributed Parallel Pursuit. CoRR abs/1403.6974 (2014) - [i20]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Distributed Quantization for Measurement of Correlated Sparse Sources over Noisy Channels. CoRR abs/1404.7640 (2014) - [i19]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Performance Bounds for Vector Quantized Compressive Sensing. CoRR abs/1404.7643 (2014) - [i18]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Channel-Optimized Vector Quantizer Design for Compressed Sensing Measurements. CoRR abs/1404.7648 (2014) - [i17]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Analysis-by-Synthesis-based Quantization of Compressed Sensing Measurements. CoRR abs/1404.7651 (2014) - [i16]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Analysis-by-Synthesis Quantization for Compressed Sensing Measurements. CoRR abs/1404.7659 (2014) - [i15]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Distributed Quantization for Compressed Sensing. CoRR abs/1404.7666 (2014) - [i14]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Joint Source-Channel Vector Quantization for Compressed Sensing. CoRR abs/1406.0086 (2014) - [i13]Kezhi Li, Cristian R. Rojas, Saikat Chatterjee, Håkan Hjalmarsson:
Piecewise Toeplitz Matrices-based Sensing for Rank Minimization. CoRR abs/1406.0187 (2014) - [i12]Martin Sundin, Saikat Chatterjee, Magnus Jansson, Cristian R. Rojas:
Relevance Singular Vector Machine for low-rank matrix sensing. CoRR abs/1407.0013 (2014) - [i11]Kezhi Li, Martin Sundin, Cristian R. Rojas, Saikat Chatterjee, Magnus Jansson:
Alternating Strategies Are Good For Low-Rank Matrix Reconstruction. CoRR abs/1407.3410 (2014) - [i10]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Analysis of Democratic Voting Principles used in Distributed Greedy Algorithms. CoRR abs/1407.4491 (2014) - 2013
- [j16]Dave Zachariah, Petter Wirfält, Magnus Jansson, Saikat Chatterjee:
Line spectrum estimation with probabilistic priors. Signal Process. 93(11): 2969-2974 (2013) - [j15]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Fusion of Algorithms for Compressed Sensing. IEEE Trans. Signal Process. 61(14): 3699-3704 (2013) - [j14]John T. Flåm, Dave Zachariah, Mikko Vehkaperä, Saikat Chatterjee:
The Linear Model Under Mixed Gaussian Inputs: Designing the Transfer Matrix. IEEE Trans. Signal Process. 61(21): 5247-5259 (2013) - [j13]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Analysis-by-Synthesis Quantization for Compressed Sensing Measurements. IEEE Trans. Signal Process. 61(22): 5789-5800 (2013) - [c41]Dave Zachariah, Magnus Jansson, Saikat Chatterjee:
Enhanced Capon beamformer using regularized covariance matching. CAMSAP 2013: 97-100 - [c40]Martin Sundin, Magnus Jansson, Saikat Chatterjee:
Conditional prior based lmmse estimation of sparse signals. EUSIPCO 2013: 1-5 - [c39]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee:
Statistical mechanics approach to sparse noise denoising. EUSIPCO 2013: 1-5 - [c38]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Parallel pursuit for distributed compressed sensing. GlobalSIP 2013: 783-786 - [c37]Dennis Sundman, Dave Zachariah, Saikat Chatterjee, Mikael Skoglund:
Distributed predictive subspace pursuit. ICASSP 2013: 4633-4637 - [c36]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Channel-optimized vector quantizer design for compressed sensing measurements. ICASSP 2013: 4648-4652 - [c35]John T. Flåm, Emil Björnson, Saikat Chatterjee:
Pilot design for MIMO channel estimation: An alternative to the Kronecker structure assumption. ICASSP 2013: 5061-5064 - [c34]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Analysis-by-synthesis-based quantization of compressed sensing measurements. ICASSP 2013: 5810-5814 - [c33]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Fusion of algorithms for Compressed Sensing. ICASSP 2013: 5860-5864 - [c32]Dave Zachariah, Saikat Chatterjee, Magnus Jansson:
Iteratively reweighted least squares for reconstruction of low-rank matrices with linear structure. ICASSP 2013: 6456-6460 - [i9]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee:
Statistical Mechanics Approach to Sparse Noise Denoising. CoRR abs/1303.4266 (2013) - [i8]Dave Zachariah, Petter Wirfält, Magnus Jansson, Saikat Chatterjee:
Line Spectrum Estimation with Probabilistic Priors. CoRR abs/1306.5883 (2013) - [i7]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Distributed Greedy Pursuit Algorithms. CoRR abs/1306.6815 (2013) - [i6]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee:
Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing. CoRR abs/1312.0256 (2013) - 2012
- [j12]Dave Zachariah, Martin Sundin, Magnus Jansson, Saikat Chatterjee:
Alternating Least-Squares for Low-Rank Matrix Reconstruction. IEEE Signal Process. Lett. 19(4): 231-234 (2012) - [j11]Saikat Chatterjee, Dennis Sundman, Mikko Vehkaperä, Mikael Skoglund:
Projection-Based and Look-Ahead Strategies for Atom Selection. IEEE Trans. Signal Process. 60(2): 634-647 (2012) - [j10]John T. Flåm, Saikat Chatterjee, Kimmo Kansanen, Torbjörn Ekman:
On MMSE Estimation: A Linear Model Under Gaussian Mixture Statistics. IEEE Trans. Signal Process. 60(7): 3840-3845 (2012) - [j9]Dave Zachariah, Saikat Chatterjee, Magnus Jansson:
Dynamic Iterative Pursuit. IEEE Trans. Signal Process. 60(9): 4967-4972 (2012) - [c31]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Fusion of Greedy Pursuits for compressed sensing signal reconstruction. EUSIPCO 2012: 1434-1438 - [c30]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
A greedy pursuit algorithm for distributed compressed sensing. ICASSP 2012: 2729-2732 - [c29]Bhavani Shankar Mysore Rama Rao, Saikat Chatterjee, Björn E. Ottersten:
Detection of sparse random signals using compressive measurements. ICASSP 2012: 3257-3260 - [c28]Dave Zachariah, Saikat Chatterjee, Magnus Jansson:
Dynamic subspace pursuit. ICASSP 2012: 3605-3608 - [c27]Amirpasha Shirazinia, Saikat Chatterjee, Mikael Skoglund:
Performance bounds for vector quantized compressive sensing. ISITA 2012: 289-293 - [c26]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee, Erik Aurell, Mikael Skoglund, Lars K. Rasmussen:
Analysis of sparse representations using bi-orthogonal dictionaries. ITW 2012: 647-651 - [c25]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
FROGS: A serial reversible greedy search algorithm. Swe-CTW 2012: 40-45 - [i5]Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee, Erik Aurell, Mikael Skoglund, Lars K. Rasmussen:
Analysis of Sparse Representations Using Bi-Orthogonal Dictionaries. CoRR abs/1204.4065 (2012) - [i4]Sooraj K. Ambat, Saikat Chatterjee, K. V. S. Hari:
Fusion of Matching Pursuits for Compressed Sensing Signal Reconstruction. CoRR abs/1204.4656 (2012) - [i3]Mikko Vehkaperä, Saikat Chatterjee, Mikael Skoglund:
Analysis of MMSE Estimation for Compressive Sensing of Block Sparse Signals. CoRR abs/1204.5707 (2012) - [i2]Yoshiyuki Kabashima, Mikko Vehkaperä, Saikat Chatterjee:
Typical l1-recovery limit of sparse vectors represented by concatenations of random orthogonal matrices. CoRR abs/1208.4696 (2012) - 2011
- [j8]Saikat Chatterjee, W. Bastiaan Kleijn:
Auditory Model-Based Design and Optimization of Feature Vectors for Automatic Speech Recognition. IEEE Trans. Speech Audio Process. 19(6): 1813-1825 (2011) - [c24]Saikat Chatterjee, Dennis Sundman, Mikko Vehkaperä, Mikael Skoglund:
Hybrid greedy pursuit. EUSIPCO 2011: 343-347 - [c23]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Greedy pursuits for compressed sensing of jointly sparse signals. EUSIPCO 2011: 368-372 - [c22]John T. Flåm, Joakim Jaldén, Saikat Chatterjee:
Gaussian mixture modeling for source localization. ICASSP 2011: 2604-2607 - [c21]Saikat Chatterjee, Dennis Sundman, Mikael Skoglund:
Look ahead orthogonal matching pursuit. ICASSP 2011: 4024-4027 - [c20]Mikko Vehkaperä, Saikat Chatterjee, Mikael Skoglund:
Analysis of MMSE estimation for compressive sensing of block sparse signals. ITW 2011: 553-557 - [c19]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
Look ahead parallel pursuit. Swe-CTW 2011: 114-117 - [i1]Saikat Chatterjee, Dennis Sundman, Mikko Vehkaperä, Mikael Skoglund:
Projection-Based and Look Ahead Strategies for Atom Selection. CoRR abs/1111.2001 (2011) - 2010
- [c18]Saikat Chatterjee, Mikael Skoglund:
Structured Gaussian mixture model based product VQ. EUSIPCO 2010: 771-775 - [c17]Christos Koniaris, Saikat Chatterjee, W. Bastiaan Kleijn:
Selecting static and dynamic features using an advanced auditory model for speech recognition. ICASSP 2010: 4342-4345 - [c16]Saikat Chatterjee, W. Bastiaan Kleijn:
Auditory model based modified MFCC features. ICASSP 2010: 4590-4593 - [c15]Joyojeet Pal, Anjali Vartak, Vrutti Vyas, Saikat Chatterjee, Nektarios Paisios, Rahul Cherian:
A ratification of means: international law and assistive technology in the developing world. ICTD 2010: 29:1-29:11 - [c14]Saikat Chatterjee, Dennis Sundman, Mikael Skoglund:
Statistical post-processing improves basis pursuit denoising performance. ISSPIT 2010: 23-27 - [c13]Dennis Sundman, Saikat Chatterjee, Mikael Skoglund:
On the use of compressive sampling for wide-band spectrum sensing. ISSPIT 2010: 354-359
2000 – 2009
- 2009
- [j7]Saikat Chatterjee, Thippur V. Sreenivas:
Reduced complexity two stage vector quantization. Digit. Signal Process. 19(3): 476-490 (2009) - [c12]Saikat Chatterjee, Thippur V. Sreenivas:
Analysis-by-synthesis based switched transform domain split VQ using Gaussian mixture model. ICASSP 2009: 4117-4120 - [c11]Saikat Chatterjee, Christos Koniaris, W. Bastiaan Kleijn:
Auditory model based optimization of MFCCs improves automatic speech recognition performance. INTERSPEECH 2009: 2987-2990 - 2008
- [j6]Saikat Chatterjee, T. V. Sreenivas:
Optimum switched split vector quantization of LSF parameters. Signal Process. 88(6): 1528-1538 (2008) - [j5]Saikat Chatterjee, Thippur V. Sreenivas:
Switched Conditional PDF-Based Split VQ Using Gaussian Mixture Model. IEEE Signal Process. Lett. 15: 91-94 (2008) - [j4]Saikat Chatterjee, Thippur V. Sreenivas:
Predicting VQ Performance Bound for LSF Coding. IEEE Signal Process. Lett. 15: 166-169 (2008) - [j3]Saikat Chatterjee, Thippur V. Sreenivas:
Optimum Transform Domain Split VQ. IEEE Signal Process. Lett. 15: 285-288 (2008) - [c10]Saikat Chatterjee, Thippur V. Sreenivas:
Low complexity wideband LSF quantization using GMM of uncorrelated Gaussian mixtures. EUSIPCO 2008: 1-5 - [c9]Achintya Kundu, Saikat Chatterjee, Thippur V. Sreenivas:
Speech enhancement using intra-frame dependency in DCT domain. EUSIPCO 2008: 1-5 - [c8]Achintya Kundu, Saikat Chatterjee, A. Sreenivasa Murthy, T. V. Sreenivas:
GMM based Bayesian approach to speech enhancement in signal / transform domain. ICASSP 2008: 4893-4896 - [c7]Achintya Kundu, Saikat Chatterjee, T. V. Sreenivas:
Subspace based speech enhancement using Gaussian mixture model. INTERSPEECH 2008: 395-398 - 2007
- [j2]Saikat Chatterjee, Thippur V. Sreenivas:
Conditional PDF-Based Split Vector Quantization of Wideband LSF Parameters. IEEE Signal Process. Lett. 14(9): 641-644 (2007) - [j1]Saikat Chatterjee, Thippur V. Sreenivas:
Analysis of Conditional PDF-Based Split VQ. IEEE Signal Process. Lett. 14(11): 781-784 (2007) - [c6]Saikat Chatterjee, Thippur V. Sreenivas:
Sequential Split Vector Quantization of LSF Parameters using Conditional Pdf. ICASSP (4) 2007: 1101-1104 - [c5]Saikat Chatterjee, Thippur V. Sreenivas:
Normalized two stage SVQ for minimum complexity wide-band LSF quantization. INTERSPEECH 2007: 1657-1660 - [c4]Saikat Chatterjee, Thippur V. Sreenivas:
Computationally efficient optimum weighting function for vector quantization of LSF parameters. ISSPA 2007: 1-4 - [c3]Saikat Chatterjee, Thippur V. Sreenivas:
Joint inter-frame and intra-frame predictive coding of LSF parameters. ISSPA 2007: 1-4 - 2006
- [c2]Saikat Chatterjee, T. V. Sreenivas:
Two stage transform vector quantization of LSFs for wideband speech coding. INTERSPEECH 2006 - [c1]Saikat Chatterjee, T. V. Sreenivas:
Comparison of prediction based LSF quantization methods using split VQ. INTERSPEECH 2006
Coauthor Index
Lars K. Rasmussen
aka: Lars Kildehoj Rasmussen
aka: Lars Kildehoj Rasmussen
[j39] [c82] [c81] [c80] [j36] [c76] [c75] [c74] [c73] [c72] [c68] [i46] [i45] [i43] [i42] [c66] [i40] [i36] [j30] [c60] [c58] [i25] [j26] [j24] [j23] [j20] [j17] [c45] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i10] [j13] [c38] [c37] [c36] [c34] [i7] [j11] [c30] [c27] [c26] [c25] [i5] [i3] [c24] [c23] [c21] [c20] [c19] [i1] [c18] [c14] [c13]
Thippur V. Sreenivas
aka: T. V. Sreenivas
aka: T. V. Sreenivas
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