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ORCIDRose Yu
Qi Rose Yu
Person information
- affiliation: University of California, San Diego, CA, USA
- affiliation (former): Northeastern University, MA, USA
- affiliation (former): Caltech, CA, USA
- affiliation (former): University of Southern California, CA, USA
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2020 – today
- 2024
[j6]Peter Eckmann
, Jake Anderson, Rose Yu, Michael K. Gilson:
Ligand-Based Compound Activity Prediction via Few-Shot Learning. J. Chem. Inf. Model. 64(14): 5492-5499 (2024)- [c58]Dongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil, Aurélie C. Lozano, Naoki Abe, Yi-An Ma, Rose Yu:
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. AISTATS 2024: 415-423 - [c57]Cai Zhou, Rose Yu, Yusu Wang:
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. AISTATS 2024: 2179-2187 - [c56]Yasaman Jafari, Dheeraj Mekala, Rose Yu, Taylor Berg-Kirkpatrick:
MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization. EMNLP (Findings) 2024: 9878-9889 - [c55]Sophia Huiwen Sun, Rose Yu:
Copula Conformal prediction for multi-step time series prediction. ICLR 2024 - [c54]Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu:
Improving Convergence and Generalization Using Parameter Symmetries. ICLR 2024 - [c53]Ruijia Niu, Dongxia Wu, Kai Kim, Yian Ma, Duncan Watson-Parris, Rose Yu:
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling. ICML 2024 - [c52]Sumanth Varambally, Yian Ma, Rose Yu:
Discovering Mixtures of Structural Causal Models from Time Series Data. ICML 2024 - [c51]Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu:
Latent Space Symmetry Discovery. ICML 2024 - [c50]Tao Wang, Bo Zhao, Sicun Gao, Rose Yu:
Understanding the difficulty of solving Cauchy problems with PINNs. L4DC 2024: 453-465 - [c49]Sophia Huiwen Sun, Wenyuan Chen, Zihao Zhou, Sonia Fereidooni, Elise Jortberg, Rose Yu:
Data-driven simulator for mechanical circulatory support with domain adversarial neural process. L4DC 2024: 1513-1525 - [i74]Dongxia Wu, Tsuyoshi Idé, Aurélie C. Lozano, Georgios Kollias, Jirí Navrátil, Naoki Abe, Yi-An Ma, Rose Yu:
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes. CoRR abs/2402.03726 (2024) - [i73]Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu:
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling. CoRR abs/2402.10387 (2024) - [i72]Yasaman Jafari, Dheeraj Mekala, Rose Yu, Taylor Berg-Kirkpatrick:
MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization. CoRR abs/2402.11711 (2024) - [i71]Ruijia Niu, Dongxia Wu, Kai Kim, Yi-An Ma, Duncan Watson-Parris, Rose Yu:
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling. CoRR abs/2402.18846 (2024) - [i70]Cai Zhou, Rose Yu, Yusu Wang:
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers. CoRR abs/2404.03380 (2024) - [i69]Tao Wang, Bo Zhao, Sicun Gao, Rose Yu:
Understanding the Difficulty of Solving Cauchy Problems with PINNs. CoRR abs/2405.02561 (2024) - [i68]Jianke Yang, Wang Rao, Nima Dehmamy, Robin Walters, Rose Yu:
Symmetry-Informed Governing Equation Discovery. CoRR abs/2405.16756 (2024) - [i67]Sophia Huiwen Sun, Wenyuan Chen, Zihao Zhou, Sonia Fereidooni, Elise Jortberg, Rose Yu:
Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process. CoRR abs/2405.18536 (2024) - [i66]Salva Rühling Cachay, Brian Henn, Oliver Watt-Meyer, Christopher S. Bretherton, Rose Yu:
Probabilistic Emulation of a Global Climate Model with Spherical DYffusion. CoRR abs/2406.14798 (2024) - [i65]Dongxia Wu, Nikki Lijing Kuang, Ruijia Niu, Yi-An Ma, Rose Yu:
Diff-BBO: Diffusion-Based Inverse Modeling for Black-Box Optimization. CoRR abs/2407.00610 (2024) - [i64]Vineet Thumuluri, Peter Eckmann, Michael K. Gilson, Rose Yu:
Technical report: Improving the properties of molecules generated by LIMO. CoRR abs/2407.14968 (2024) - [i63]Minxuan Duan, Yinlong Qian, Lingyi Zhao, Zihao Zhou, Zeeshan Rasheed, Rose Yu, Khurram Shafique:
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework. CoRR abs/2410.01011 (2024) - [i62]Zihao Zhou, Rose Yu:
Can LLMs Understand Time Series Anomalies? CoRR abs/2410.05440 (2024) - [i61]Ruijia Niu, Dongxia Wu, Rose Yu, Yi-An Ma:
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs. CoRR abs/2410.06431 (2024) - [i60]Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu:
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning. CoRR abs/2410.11226 (2024) - [i59]Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick:
ClimaQA: An Automated Evaluation Framework for Climate Foundation Models. CoRR abs/2410.16701 (2024) - [i58]Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick, Rose Yu:
Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation. CoRR abs/2411.00412 (2024) - 2023
- [j5]Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp:
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. Nat. Mac. Intell. 5(11): 1326-1335 (2023) - [j4]Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu:
Long-term Forecasting with TiDE: Time-series Dense Encoder. Trans. Mach. Learn. Res. 2023 (2023) - [c48]Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu:
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts. ICLR 2023 - [c47]Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu, Nima Dehmamy:
Symmetries, Flat Minima, and the Conserved Quantities of Gradient Flow. ICLR 2023 - [c46]Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang:
On the Connection Between MPNN and Graph Transformer. ICML 2023: 3408-3430 - [c45]Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu:
Disentangled Multi-Fidelity Deep Bayesian Active Learning. ICML 2023: 37624-37634 - [c44]Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu:
Generative Adversarial Symmetry Discovery. ICML 2023: 39488-39508 - [c43]Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Deep Bayesian Active Learning for Accelerating Stochastic Simulation. KDD 2023: 2559-2569 - [c42]Naoki Abe, Kathleen Buckingham, Yuzhou Chen, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, Yulia R. Gel, James Hodson, Ramakrishnan Kannan, Huikyo Lee, Jiafu Mao, Rose Yu:
Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond. KDD 2023: 5845-5846 - [c41]Zihao Zhou, Rose Yu:
Automatic Integration for Fast and Interpretable Neural Point Processes. L4DC 2023: 573-585 - [c40]Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu:
Probabilistic Symmetry for Multi-Agent Dynamics. L4DC 2023: 1231-1244 - [c39]Salva Rühling Cachay, Bo Zhao, Hailey Joren, Rose Yu:
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting. NeurIPS 2023 - [c38]Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard:
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS 2023 - [c37]Zihao Zhou, Rose Yu:
Automatic Integration for Spatiotemporal Neural Point Processes. NeurIPS 2023 - [c36]Mathias Niemann Tygesen, Mayank Sharan, Francisco C. Pereira, Filipe Rodrigues, Rose Yu:
Incident congestion propagation prediction using incident reports. SuMob@SIGSPATIAL 2023: 33-42 - [i57]Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang:
On the Connection Between MPNN and Graph Transformer. CoRR abs/2301.11956 (2023) - [i56]Jianke Yang, Robin Walters, Nima Dehmamy, Rose Yu:
Generative Adversarial Symmetry Discovery. CoRR abs/2302.00236 (2023) - [i55]Alejandro Rodriguez Pascual, Ishan Mehta, Muhammad Khan, Frank Rodriz, Rose Yu:
Understanding why shooters shoot - An AI-powered engine for basketball performance profiling. CoRR abs/2303.09715 (2023) - [i54]Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu:
Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR abs/2304.08424 (2023) - [i53]Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu:
Disentangled Multi-Fidelity Deep Bayesian Active Learning. CoRR abs/2305.04392 (2023) - [i52]Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu:
Improving Convergence and Generalization Using Parameter Symmetries. CoRR abs/2305.13404 (2023) - [i51]Salva Rühling Cachay, Bo Zhao, Hailey James, Rose Yu:
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting. CoRR abs/2306.01984 (2023) - [i50]Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.:
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR abs/2306.08754 (2023) - [i49]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i48]Jianke Yang, Nima Dehmamy, Robin Walters, Rose Yu:
Latent Space Symmetry Discovery. CoRR abs/2310.00105 (2023) - [i47]Zihao Zhou, Rose Yu:
Automatic Integration for Spatiotemporal Neural Point Processes. CoRR abs/2310.06179 (2023) - [i46]Sumanth Varambally, Yi-An Ma, Rose Yu:
Discovering Mixtures of Structural Causal Models from Time Series Data. CoRR abs/2310.06312 (2023) - [i45]Peter Eckmann, Jake Anderson, Michael K. Gilson, Rose Yu:
Target-Free Compound Activity Prediction via Few-Shot Learning. CoRR abs/2311.16328 (2023) - 2022
- [j3]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. Patterns 3(10): 100588 (2022) - [c35]Utkrisht Rajkumar, Sara Javadzadeh, Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, Vineet Bafna:
DeepViFi: detecting oncoviral infections in cancer genomes using transformers. BCB 2022: 2:1-2:8 - [c34]Alan Li, Zihao Zhou, Elise Jortberg, Rose Yu:
Forecasting Aortic Pressure Cross-Cohort with Deep Sequence Models. CinC 2022: 1-4 - [c33]Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu:
LIMO: Latent Inceptionism for Targeted Molecule Generation. ICML 2022: 5777-5792 - [c32]Rui Wang, Robin Walters, Rose Yu:
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. ICML 2022: 23078-23091 - [c31]Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Multi-fidelity Hierarchical Neural Processes. KDD 2022: 2029-2038 - [c30]Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu:
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice. KDD 2022: 4866-4867 - [c29]Zihao Zhou, Xingyi Yang, Ryan A. Rossi, Handong Zhao, Rose Yu:
Neural Point Process for Learning Spatiotemporal Event Dynamics. L4DC 2022: 777-789 - [c28]Rui Wang, Robin Walters, Rose Yu:
Meta-Learning Dynamics Forecasting Using Task Inference. NeurIPS 2022 - [c27]Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu:
Symmetry Teleportation for Accelerated Optimization. NeurIPS 2022 - [i44]Rui Wang, Robin Walters, Rose Yu:
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. CoRR abs/2201.11969 (2022) - [i43]Jedrzej Kozerawski, Mayank Sharan, Rose Yu:
Taming the Long Tail of Deep Probabilistic Forecasting. CoRR abs/2202.13418 (2022) - [i42]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. CoRR abs/2204.00056 (2022) - [i41]Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu:
Probabilistic Symmetry for Improved Trajectory Forecasting. CoRR abs/2205.01927 (2022) - [i40]Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu:
Symmetry Teleportation for Accelerated Optimization. CoRR abs/2205.10637 (2022) - [i39]Nima Dehmamy, Csaba Both, Jianzhi Long, Rose Yu:
Faster Optimization on Sparse Graphs via Neural Reparametrization. CoRR abs/2205.13624 (2022) - [i38]Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Multi-fidelity Hierarchical Neural Processes. CoRR abs/2206.04872 (2022) - [i37]Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu:
LIMO: Latent Inceptionism for Targeted Molecule Generation. CoRR abs/2206.09010 (2022) - [i36]Rui Wang, Robin Walters, Rose Yu:
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting. CoRR abs/2206.09450 (2022) - [i35]Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp:
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. CoRR abs/2210.00881 (2022) - [i34]Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu:
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts. CoRR abs/2210.03675 (2022) - [i33]Bo Zhao, Iordan Ganev, Robin Walters, Rose Yu, Nima Dehmamy:
Symmetries, flat minima, and the conserved quantities of gradient flow. CoRR abs/2210.17216 (2022) - [i32]Sophia Huiwen Sun, Rose Yu:
Copula Conformal Prediction for Multi-step Time Series Forecasting. CoRR abs/2212.03281 (2022) - 2021
- [c26]Robin Walters, Jinxi Li, Rose Yu:
Trajectory Prediction using Equivariant Continuous Convolution. ICLR 2021 - [c25]Rui Wang, Robin Walters, Rose Yu:
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. ICLR 2021 - [c24]Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. KDD 2021: 1841-1851 - [c23]Rose Yu, Paris Perdikaris, Anuj Karpatne:
Physics-Guided AI for Large-Scale Spatiotemporal Data. KDD 2021: 4088-4089 - [c22]Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash:
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD 2021: 4104-4105 - [c21]Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu:
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. L4DC 2021: 385-398 - [c20]Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu:
Traffic Forecasting using Vehicle-to-Vehicle Communication. L4DC 2021: 917-929 - [c19]Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu:
Automatic Symmetry Discovery with Lie Algebra Convolutional Network. NeurIPS 2021: 2503-2515 - [i31]Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting. CoRR abs/2102.06684 (2021) - [i30]Rui Wang, Robin Walters, Rose Yu:
Meta-Learning Dynamics Forecasting Using Task Inference. CoRR abs/2102.10271 (2021) - [i29]Niklas Smedemark-Margulies, Jung Yeon Park, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand:
Generator Surgery for Compressed Sensing. CoRR abs/2102.11163 (2021) - [i28]Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu:
Traffic Forecasting using Vehicle-to-Vehicle Communication. CoRR abs/2104.05528 (2021) - [i27]Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. CoRR abs/2105.11982 (2021) - [i26]Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Accelerating Stochastic Simulation with Interactive Neural Processes. CoRR abs/2106.02770 (2021) - [i25]Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu:
Automatic Symmetry Discovery with Lie Algebra Convolutional Network. CoRR abs/2109.07103 (2021) - [i24]Zihao Zhou, Xingyi Yang, Ryan A. Rossi, Handong Zhao, Rose Yu:
Neural Point Process for Learning Spatiotemporal Event Dynamics. CoRR abs/2112.06351 (2021) - [i23]Ayan Chatterjee, Omair Shafi Ahmed, Robin Walters, Zohair Shafi, Deisy Morselli Gysi, Rose Yu, Tina Eliassi-Rad, Albert-László Barabási, Giulia Menichetti:
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands. CoRR abs/2112.13168 (2021) - 2020
- [c18]Eliza Huang, Rui Wang, Uma Chandrasekaran, Rose Yu:
Aortic Pressure Forecasting With Deep Learning. CinC 2020: 1-4 - [c17]Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu:
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. ICML 2020: 7499-7509 - [c16]Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu:
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. KDD 2020: 1457-1466 - [c15]Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu:
Deep Imitation Learning for Bimanual Robotic Manipulation. NeurIPS 2020 - [c14]Armand Comas Massague, Chi Zhang, Zlatan Feric, Octavia I. Camps, Rose Yu:
Learning Disentangled Representations of Videos with Missing Data. NeurIPS 2020 - [i22]Rui Wang, Robin Walters, Rose Yu:
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. CoRR abs/2002.03061 (2020) - [i21]Jung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu:
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. CoRR abs/2002.05578 (2020) - [i20]Rui Wang, Eliza Huang, Uma Chandrasekaran, Rose Yu:
Aortic Pressure Forecasting with Deep Sequence Learning. CoRR abs/2005.05502 (2020) - [i19]Chintan Shah, Nima Dehmamy, Nicola Perra, Matteo Chinazzi, Albert-László Barabási, Alessandro Vespignani, Rose Yu:
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks. CoRR abs/2006.11913 (2020) - [i18]Armand Comas Massague, Chi Zhang, Zlatan Feric, Octavia I. Camps, Rose Yu:
Learning Disentangled Representations of Video with Missing Data. CoRR abs/2006.13391 (2020) - [i17]Ruichao Xiao, Rose Yu:
Dynamic Relational Inference in Multi-Agent Trajectories. CoRR abs/2007.13524 (2020) - [i16]Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu:
Deep Imitation Learning for Bimanual Robotic Manipulation. CoRR abs/2010.05134 (2020) - [i15]Robin Walters, Jinxi Li, Rose Yu:
Trajectory Prediction using Equivariant Continuous Convolution. CoRR abs/2010.11344 (2020) - [i14]Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu:
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. CoRR abs/2011.10616 (2020)
2010 – 2019
- 2019
- [c13]Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural Lander: Stable Drone Landing Control Using Learned Dynamics. ICRA 2019: 9784-9790 - [c12]Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue:
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. NeurIPS 2019: 11236-11246 - [c11]Nima Dehmamy, Albert-László Barabási, Rose Yu:
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology. NeurIPS 2019: 15387-15397 - [i13]Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue:
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. CoRR abs/1901.10946 (2019) - [i12]Nima Dehmamy, Albert-László Barabási, Rose Yu:
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology. CoRR abs/1907.05008 (2019) - [i11]Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu:
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. CoRR abs/1911.08655 (2019) - 2018
- [c10]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. AISTATS 2018: 482-490 - [c9]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. ICLR (Poster) 2018 - [i10]Stephan Zheng, Rose Yu, Yisong Yue:
Multi-resolution Tensor Learning for Large-Scale Spatial Data. CoRR abs/1802.06825 (2018) - [i9]Sung-En Chang, Xun Zheng, Ian En-Hsu Yen, Pradeep Ravikumar, Rose Yu:
Learning Tensor Latent Features. CoRR abs/1810.04754 (2018) - [i8]Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung:
Neural Lander: Stable Drone Landing Control using Learned Dynamics. CoRR abs/1811.08027 (2018) - 2017
- [c8]Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu:
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. SDM 2017: 777-785 - [r1]Rose Yu, Yan Liu:
Spatiotemporal Analysis of Social Media Data. Encyclopedia of GIS 2017: 2126-2133 - [i7]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. CoRR abs/1707.01926 (2017) - [i6]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. CoRR abs/1710.11345 (2017) - [i5]Rose Yu, Stephan Zheng, Anima Anandkumar, Yisong Yue:
Long-term Forecasting using Tensor-Train RNNs. CoRR abs/1711.00073 (2017) - 2016
- [j2]Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu:
A Survey on Social Media Anomaly Detection. SIGKDD Explor. 18(1): 1-14 (2016) - [c7]Rose Yu, Yan Liu:
Learning from Multiway Data: Simple and Efficient Tensor Regression. ICML 2016: 373-381 - [c6]Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu:
Latent Space Model for Road Networks to Predict Time-Varying Traffic. KDD 2016: 1525-1534 - [c5]Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu:
Geographic Segmentation via Latent Poisson Factor Model. WSDM 2016: 357-366 - [i4]Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu:
A Survey on Social Media Anomaly Detection. CoRR abs/1601.01102 (2016) - [i3]Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu:
Latent Space Model for Road Networks to Predict Time-Varying Traffic. CoRR abs/1602.04301 (2016) - [i2]Qi Rose Yu, Yan Liu:
Learning from Multiway Data: Simple and Efficient Tensor Regression. CoRR abs/1607.02535 (2016) - [i1]Rose Yu, Paroma Varma, Dan Iter, Christopher De Sa, Christopher Ré:
Socratic Learning. CoRR abs/1610.08123 (2016) - 2015
- [j1]Rose Yu, Xinran He, Yan Liu:
GLAD: Group Anomaly Detection in Social Media Analysis. ACM Trans. Knowl. Discov. Data 10(2): 18:1-18:22 (2015) - [c4]Rose Yu, Dehua Cheng, Yan Liu:
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. ICML 2015: 238-247 - 2014
- [c3]Qi Rose Yu, Xinran He, Yan Liu:
GLAD: group anomaly detection in social media analysis. KDD 2014: 372-381 - [c2]Mohammad Taha Bahadori, Qi Rose Yu, Yan Liu:
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning. NIPS 2014: 3491-3499 - 2011
- [c1]Cuixia Gao, Naiyan Wang, Qi Rose Yu, Zhihua Zhang:
A Feasible Nonconvex Relaxation Approach to Feature Selection. AAAI 2011: 356-361
Coauthor Index
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