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ORCIDMathias Niepert
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- affiliation: University of Stuttgart, Germany
- affiliation: NEC Laboratories Europe, Heidelberg, Germany
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2020 – today
- 2024
[j12]Giuseppe Serra, Mathias Niepert
:
L2XGNN: learning to explain graph neural networks. Mach. Learn. 113(9): 6787-6809 (2024)- [c85]Federico Errica, Mathias Niepert:
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks. ICLR 2024 - [c84]Anji Liu, Mathias Niepert, Guy Van den Broeck:
Image Inpainting via Tractable Steering of Diffusion Models. ICLR 2024 - [c83]Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris:
Probabilistically Rewired Message-Passing Neural Networks. ICLR 2024 - [c82]Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp, Mathias Niepert:
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations. ICML 2024 - [c81]Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert:
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. ICML 2024 - [i74]Anji Liu, Mathias Niepert, Guy Van den Broeck:
Image Inpainting via Tractable Steering of Diffusion Models. CoRR abs/2401.03349 (2024) - [i73]Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert:
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. CoRR abs/2402.01975 (2024) - [i72]Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing. CoRR abs/2405.14253 (2024) - [i71]Vinh Tong, Anji Liu, Trung-Dung Hoang, Guy Van den Broeck, Mathias Niepert:
Learning to Discretize Denoising Diffusion ODEs. CoRR abs/2405.15506 (2024) - [i70]Hoai-Chau Tran, Duy M. H. Nguyen, Duy M. Nguyen, TrungTin Nguyen, Ngan Le, Pengtao Xie, Daniel Sonntag, James Y. Zou, Binh T. Nguyen, Mathias Niepert:
Accelerating Transformers with Spectrum-Preserving Token Merging. CoRR abs/2405.16148 (2024) - [i69]Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert:
Probabilistic Graph Rewiring via Virtual Nodes. CoRR abs/2405.17311 (2024) - [i68]Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp, Mathias Niepert:
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations. CoRR abs/2406.03919 (2024) - [i67]Duy M. H. Nguyen, An T. Le, Trung Q. Nguyen, Nghiem T. Diep, Tai Nguyen, Duy Duong-Tran, Jan Peters, Li Shen, Mathias Niepert, Daniel Sonntag:
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model. CoRR abs/2407.04489 (2024) - [i66]Daniel Musekamp, Marimuthu Kalimuthu, David Holzmüller, Makoto Takamoto, Mathias Niepert:
Active Learning for Neural PDE Solvers. CoRR abs/2408.01536 (2024) - [i65]Makoto Takamoto, Viktor Zaverkin, Mathias Niepert:
Physics-Informed Weakly Supervised Learning for Interatomic Potentials. CoRR abs/2408.05215 (2024) - [i64]Laurène Vaugrante, Mathias Niepert, Thilo Hagendorff:
A Looming Replication Crisis in Evaluating Behavior in Language Models? Evidence and Solutions. CoRR abs/2409.20303 (2024) - [i63]Anji Liu, Oliver Broadrick, Mathias Niepert, Guy Van den Broeck:
Discrete Copula Diffusion. CoRR abs/2410.01949 (2024) - [i62]Duy M. H. Nguyen, Nghiem T. Diep, Trung Q. Nguyen, Hoang-Bao Le, Tai Nguyen, Tien Nguyen, TrungTin Nguyen, Nhat Ho, Pengtao Xie, Roger Wattenhofer, James Zhou, Daniel Sonntag, Mathias Niepert:
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model. CoRR abs/2410.02615 (2024) - [i61]Andrei Manolache, Dragos Tantaru, Mathias Niepert:
MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning. CoRR abs/2410.07981 (2024) - 2023
- [j11]Cheng Wang, Carolin Lawrence, Mathias Niepert:
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7739-7750 (2023) - [c80]Pasquale Minervini, Luca Franceschi, Mathias Niepert:
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. AAAI 2023: 9200-9208 - [c79]Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck:
SIMPLE: A Gradient Estimator for k-Subset Sampling. ICLR 2023 - [c78]Makoto Takamoto, Francesco Alesiani, Mathias Niepert:
Learning Neural PDE Solvers with Parameter-Guided Channel Attention. ICML 2023: 33448-33467 - [c77]Duy M. H. Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert:
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching. NeurIPS 2023 - [c76]David Friede, Christian Reimers, Heiner Stuckenschmidt, Mathias Niepert:
Learning Disentangled Discrete Representations. ECML/PKDD (4) 2023: 593-609 - [p1]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. Compendium of Neurosymbolic Artificial Intelligence 2023: 373-386 - [i60]Zhao Xu, Daniel Oñoro-Rubio, Giuseppe Serra, Mathias Niepert:
Learning Sparsity of Representations with Discrete Latent Variables. CoRR abs/2304.00935 (2023) - [i59]Makoto Takamoto, Francesco Alesiani, Mathias Niepert:
Learning Neural PDE Solvers with Parameter-Guided Channel Attention. CoRR abs/2304.14118 (2023) - [i58]Federico Errica, Mathias Niepert:
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks. CoRR abs/2305.10544 (2023) - [i57]Duy M. H. Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert:
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching. CoRR abs/2306.11925 (2023) - [i56]David Friede, Christian Reimers, Heiner Stuckenschmidt, Mathias Niepert:
Learning Disentangled Discrete Representations. CoRR abs/2307.14151 (2023) - [i55]David Friede, Mathias Niepert:
Efficient Learning of Discrete-Continuous Computation Graphs. CoRR abs/2307.14193 (2023) - [i54]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. CoRR abs/2308.06585 (2023) - [i53]Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris:
Probabilistically Rewired Message-Passing Neural Networks. CoRR abs/2310.02156 (2023) - [i52]Francesco Alesiani, Shujian Yu, Mathias Niepert:
Continual Invariant Risk Minimization. CoRR abs/2310.13977 (2023) - [i51]Duy Minh Ho Nguyen, Tan Ngoc Pham, Nghiem Tuong Diep, Nghi Quoc Phan, Quang Pham, Vinh Tong, Binh T. Nguyen, Ngan Hoang Le, Nhat Ho, Pengtao Xie, Daniel Sonntag, Mathias Niepert:
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation. CoRR abs/2311.11096 (2023) - [i50]Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani:
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching. CoRR abs/2312.16560 (2023) - 2022
- [c75]Niklas Friedrich, Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavas:
AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark. ACL (demo) 2022: 44-60 - [c74]Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavas:
BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation. ACL (1) 2022: 4472-4490 - [c73]Bhushan Kotnis, Kiril Gashteovski, Daniel Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence:
MILIE: Modular & Iterative Multilingual Open Information Extraction. ACL (1) 2022: 6939-6950 - [c72]Vinh Tong, Dat Quoc Nguyen, Trung Thanh Huynh, Tam Thanh Nguyen, Quoc Viet Hung Nguyen, Mathias Niepert:
Joint Multilingual Knowledge Graph Completion and Alignment. EMNLP (Findings) 2022: 4646-4658 - [c71]Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris:
Ordered Subgraph Aggregation Networks. NeurIPS 2022 - [c70]Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert:
PDEBench: An Extensive Benchmark for Scientific Machine Learning. NeurIPS 2022 - [i49]Chendi Qian, Gaurav Rattan, Floris Geerts, Christopher Morris, Mathias Niepert:
Ordered Subgraph Aggregation Networks. CoRR abs/2206.11168 (2022) - [i48]Pasquale Minervini, Luca Franceschi, Mathias Niepert:
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. CoRR abs/2209.04862 (2022) - [i47]Giuseppe Serra, Mathias Niepert:
Learning to Explain Graph Neural Networks. CoRR abs/2209.14402 (2022) - [i46]Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck:
SIMPLE: A Gradient Estimator for k-Subset Sampling. CoRR abs/2210.01941 (2022) - [i45]Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert:
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning. CoRR abs/2210.07182 (2022) - [i44]Vinh Tong, Dat Quoc Nguyen, Thanh Trung Huynh, Thanh Tam Nguyen, Nguyen Quoc Viet Hung, Mathias Niepert:
Joint Multilingual Knowledge Graph Completion and Alignment. CoRR abs/2210.08922 (2022) - [i43]Cheng Wang, Carolin Lawrence, Mathias Niepert:
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions. CoRR abs/2212.05178 (2022) - 2021
- [c69]Bhushan Kotnis, Carolin Lawrence, Mathias Niepert:
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. AAAI 2021: 4968-4977 - [c68]Carolin Lawrence, Timo Sztyler, Mathias Niepert:
Explaining Neural Matrix Factorization with Gradient Rollback. AAAI 2021: 4987-4995 - [c67]Wiem Ben Rim, Carolin Lawrence, Kiril Gashteovski, Mathias Niepert, Naoaki Okazaki:
Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction. AKBC 2021 - [c66]Alexander Jung, Hugo Lefeuvre, Charalampos Rotsos, Pierre Olivier, Daniel Oñoro-Rubio, Felipe Huici, Mathias Niepert:
Wayfinder: towards automatically deriving optimal OS configurations. APSys 2021: 115-122 - [c65]Roberto Gonzalez, Claudio Soriente, Juan Miguel Carrascosa, Alberto García-Durán, Costas Iordanou, Mathias Niepert:
User profiling by network observers. CoNEXT 2021: 212-222 - [c64]Cheng Wang, Carolin Lawrence, Mathias Niepert:
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. ICLR 2021 - [c63]Giuseppe Serra, Zhao Xu, Mathias Niepert, Carolin Lawrence, Peter Tiño, Xin Yao:
Interpreting Node Embedding with Text-labeled Graphs. IJCNN 2021: 1-8 - [c62]Zhao Xu, Daniel Oñoro-Rubio, Giuseppe Serra, Mathias Niepert:
Learning Sparsity of Representations with Discrete Latent Variables. IJCNN 2021: 1-9 - [c61]Patrick Betz, Mathias Niepert, Pasquale Minervini, Heiner Stuckenschmidt:
Backpropagating through Markov Logic Networks. NeSy 2021: 67-81 - [c60]David Friede, Mathias Niepert:
Efficient Learning of Discrete-Continuous Computation Graphs. NeurIPS 2021: 6720-6732 - [c59]Mathias Niepert, Pasquale Minervini, Luca Franceschi:
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. NeurIPS 2021: 14567-14579 - [i42]Mathias Niepert, Pasquale Minervini, Luca Franceschi:
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. CoRR abs/2106.01798 (2021) - [i41]Jun Cheng, Carolin Lawrence, Mathias Niepert:
VEGN: Variant Effect Prediction with Graph Neural Networks. CoRR abs/2106.13642 (2021) - [i40]Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Goran Glavas, Mathias Niepert:
BenchIE: Open Information Extraction Evaluation Based on Facts, Not Tokens. CoRR abs/2109.06850 (2021) - [i39]Niklas Friedrich, Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavas:
AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark. CoRR abs/2109.07464 (2021) - [i38]Bhushan Kotnis, Kiril Gashteovski, Carolin Lawrence, Daniel Oñoro-Rubio, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert:
Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction. CoRR abs/2110.08144 (2021) - 2020
- [j10]Cheng Wang, Mathias Niepert, Hui Li:
RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems. IEEE Trans. Neural Networks Learn. Syst. 31(8): 2731-2740 (2020) - [c58]Alberto García-Durán, Roberto Gonzalez, Daniel Oñoro-Rubio, Mathias Niepert, Hui Li:
TransRev: Modeling Reviews as Translations from Users to Items. ECIR (1) 2020: 234-248 - [i37]Bhushan Kotnis, Carolin Lawrence, Mathias Niepert:
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. CoRR abs/2004.02596 (2020) - [i36]Carolin Lawrence, Timo Sztyler, Mathias Niepert:
Explaining Neural Matrix Factorization with Gradient Rollback. CoRR abs/2010.05516 (2020) - [i35]Cheng Wang, Carolin Lawrence, Mathias Niepert:
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. CoRR abs/2011.12010 (2020)
2010 – 2019
- 2019
- [c57]Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán, Roberto Gonzalez-Sanchez, Roberto Javier López-Sastre:
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs. AKBC 2019 - [c56]A. Sargeant, Tatiana von Landesberger, C. Baier, F. Bange, A. Dalpke, T. Eckmanns, Stephan Glöckner, M. Kaase, Gérard Krause, Michael Marschollek, Brandon M. Malone, Mathias Niepert, S. Rey, Antje Wulff, Simone Scheithauer:
Early Detection of Infection Chains & Outbreaks: Use Case Infection Control. EFMI-STC 2019: 245-246 - [c55]Carolin Lawrence, Bhushan Kotnis, Mathias Niepert:
Attending to Future Tokens for Bidirectional Sequence Generation. EMNLP/IJCNLP (1) 2019: 1-10 - [c54]Kosuke Akimoto, Takuya Hiraoka, Kunihiko Sadamasa, Mathias Niepert:
Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas. EMNLP/IJCNLP (1) 2019: 6224-6230 - [c53]Ye Liu, Hui Li, Alberto García-Durán, Mathias Niepert, Daniel Oñoro-Rubio, David S. Rosenblum:
MMKG: Multi-modal Knowledge Graphs. ESWC 2019: 459-474 - [c52]Luca Franceschi, Mathias Niepert, Massimiliano Pontil, Xiao He:
Learning Discrete Structures for Graph Neural Networks. ICML 2019: 1972-1982 - [c51]Cheng Wang, Mathias Niepert:
State-Regularized Recurrent Neural Networks. ICML 2019: 6596-6606 - [c50]Sebastijan Dumancic, Alberto García-Durán, Mathias Niepert:
A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning. IJCAI 2019: 6088-6094 - [i34]Cheng Wang, Mathias Niepert:
State-Regularized Recurrent Neural Networks. CoRR abs/1901.08817 (2019) - [i33]Ye Liu, Hui Li, Alberto García-Durán, Mathias Niepert, Daniel Oñoro-Rubio, David S. Rosenblum:
MMKG: Multi-Modal Knowledge Graphs. CoRR abs/1903.05485 (2019) - [i32]Cheng Wang, Mathias Niepert, Hui Li:
RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems. CoRR abs/1903.10794 (2019) - [i31]Luca Franceschi, Mathias Niepert, Massimiliano Pontil, Xiao He:
Learning Discrete Structures for Graph Neural Networks. CoRR abs/1903.11960 (2019) - [i30]Carolin Lawrence, Bhushan Kotnis, Mathias Niepert:
Attending to Future Tokens For Bidirectional Sequence Generation. CoRR abs/1908.05915 (2019) - 2018
- [c49]Daniel Oñoro-Rubio, Roberto Javier López-Sastre, Mathias Niepert:
Learning Short-Cut Connections for Object Counting. BMVC 2018: 262 - [c48]Brandon M. Malone, Alberto García-Durán, Mathias Niepert:
Knowledge Graph Completion to Predict Polypharmacy Side Effects. DILS 2018: 144-149 - [c47]Mathias Niepert, Alberto García-Durán:
Towards a Spectrum of Graph Convolutional Networks. DSW 2018: 244-248 - [c46]Cheng Wang, Mathias Niepert, Hui Li:
LRMM: Learning to Recommend with Missing Modalities. EMNLP 2018: 3360-3370 - [c45]Alberto García-Durán, Sebastijan Dumancic, Mathias Niepert:
Learning Sequence Encoders for Temporal Knowledge Graph Completion. EMNLP 2018: 4816-4821 - [c44]Alberto García-Durán, Mathias Niepert:
KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features. UAI 2018: 372-381 - [i29]Alberto García-Durán, Roberto Gonzalez, Daniel Oñoro-Rubio, Mathias Niepert, Hui Li:
TransRev: Modeling Reviews as Translations from Users to Items. CoRR abs/1801.10095 (2018) - [i28]Florian Schmidt, Mathias Niepert, Felipe Huici:
Representation Learning for Resource Usage Prediction. CoRR abs/1802.00673 (2018) - [i27]Nicolas Weber, Florian Schmidt, Mathias Niepert, Felipe Huici:
BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism. CoRR abs/1804.08378 (2018) - [i26]Mathias Niepert, Alberto García-Durán:
Towards a Spectrum of Graph Convolutional Networks. CoRR abs/1805.01837 (2018) - [i25]Daniel Oñoro-Rubio, Mathias Niepert, Roberto Javier López-Sastre:
Learning Short-Cut Connections for Object Counting. CoRR abs/1805.02919 (2018) - [i24]Daniel Oñoro-Rubio, Mathias Niepert:
Contextual Hourglass Networks for Segmentation and Density Estimation. CoRR abs/1806.04009 (2018) - [i23]Sebastijan Dumancic, Alberto García-Durán, Mathias Niepert:
On embeddings as an alternative paradigm for relational learning. CoRR abs/1806.11391 (2018) - [i22]Cheng Wang, Mathias Niepert, Hui Li:
LRMM: Learning to Recommend with Missing Modalities. CoRR abs/1808.06791 (2018) - [i21]Alberto García-Durán, Sebastijan Dumancic, Mathias Niepert:
Learning Sequence Encoders for Temporal Knowledge Graph Completion. CoRR abs/1809.03202 (2018) - [i20]Brandon M. Malone, Alberto García-Durán, Mathias Niepert:
Knowledge Graph Completion to Predict Polypharmacy Side Effects. CoRR abs/1810.09227 (2018) - [i19]Brandon M. Malone, Alberto García-Durán, Mathias Niepert:
Learning Representations of Missing Data for Predicting Patient Outcomes. CoRR abs/1811.04752 (2018) - 2017
- [j9]Jakob Huber, Mathias Niepert, Jan Noessner, Joerg Schoenfisch, Christian Meilicke, Heiner Stuckenschmidt:
An infrastructure for probabilistic reasoning with web ontologies. Semantic Web 8(2): 255-269 (2017) - [c43]Alberto García-Durán, Mathias Niepert:
Learning Graph Representations with Embedding Propagation. NIPS 2017: 5119-5130 - [c42]Roberto Gonzalez, Filipe Manco, Alberto García-Durán, Jose Mendes, Felipe Huici, Saverio Niccolini, Mathias Niepert:
Net2Vec: Deep Learning for the Network. Big-DAMA@SIGCOMM 2017: 13-18 - [c41]Roberto Gonzalez, Alberto García-Durán, Filipe Manco, Mathias Niepert, Pelayo Vallina:
Network Data Monetization Using Net2Vec. SIGCOMM Posters and Demos 2017: 37-39 - [i18]Roberto Gonzalez, Filipe Manco, Alberto García-Durán, Jose Mendes, Felipe Huici, Saverio Niccolini, Mathias Niepert:
Net2Vec: Deep Learning for the Network. CoRR abs/1705.03881 (2017) - [i17]Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán, Roberto Gonzalez, Roberto Javier López-Sastre:
Representation Learning for Visual-Relational Knowledge Graphs. CoRR abs/1709.02314 (2017) - [i16]Alberto García-Durán, Mathias Niepert:
KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features. CoRR abs/1709.04676 (2017) - [i15]Alberto García-Durán, Mathias Niepert:
Learning Graph Representations with Embedding Propagation. CoRR abs/1710.03059 (2017) - 2016
- [c40]Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov:
Learning Convolutional Neural Networks for Graphs. ICML 2016: 2014-2023 - [c39]Mathias Niepert:
Discriminative Gaifman Models. NIPS 2016: 3405-3413 - [i14]Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov:
Learning Convolutional Neural Networks for Graphs. CoRR abs/1605.05273 (2016) - [i13]Mathias Niepert:
Discriminative Gaifman Models. CoRR abs/1610.09369 (2016) - 2015
- [c38]Guy Van den Broeck, Mathias Niepert:
Lifted Probabilistic Inference for Asymmetric Graphical Models. AAAI 2015: 3599-3605 - [c37]Mathias Niepert, Pedro M. Domingos:
Learning and Inference in Tractable Probabilistic Knowledge Bases. UAI 2015: 632-641 - 2014
- [j8]Marc Gyssens, Mathias Niepert, Dirk Van Gucht:
On the completeness of the semigraphoid axioms for deriving arbitrary from saturated conditional independence statements. Inf. Process. Lett. 114(11): 628-633 (2014) - [c36]Mathias Niepert, Guy Van den Broeck:
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference. AAAI 2014: 2467-2475 - [c35]Mathias Niepert, Pedro M. Domingos:
Tractable Probabilistic Knowledge Bases: Wikipedia and Beyond. StarAI@AAAI 2014 - [c34]Mathias Niepert, Pedro M. Domingos:
Exchangeable Variable Models. ICML 2014: 271-279 - [c33]Timo Sztyler, Jakob Huber, Jan Noessner, Jaimie Murdock, Colin Allen, Mathias Niepert:
LODE: Linking digital humanities content to the web of data. JCDL 2014: 423-424 - [c32]Jan Noessner, Heiner Stuckenschmidt, Christian Meilicke, Mathias Niepert:
Completeness and optimality in ontology alignment debugging. OM 2014: 25-36 - [i12]Mathias Niepert, Guy Van den Broeck:
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference. CoRR abs/1401.1247 (2014) - [i11]Mathias Niepert, Pedro M. Domingos:
Exchangeable Variable Models. CoRR abs/1405.0501 (2014) - [i10]Jakob Huber, Timo Sztyler, Jan Noessner, Jaimie Murdock, Colin Allen, Mathias Niepert:
LODE: Linking Digital Humanities Content to the Web of Data. CoRR abs/1406.0216 (2014) - [i9]Mathias Niepert, Dirk Van Gucht, Marc Gyssens:
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach. CoRR abs/1408.2030 (2014) - [i8]Mathias Niepert:
Markov Chains on Orbits of Permutation Groups. CoRR abs/1408.2052 (2014) - [i7]Guy Van den Broeck, Mathias Niepert:
Lifted Probabilistic Inference for Asymmetric Graphical Models. CoRR abs/1412.0315 (2014) - 2013
- [j7]Mathias Niepert, Marc Gyssens, Bassem Sayrafi, Dirk Van Gucht:
On the conditional independence implication problem: A lattice-theoretic approach. Artif. Intell. 202: 29-51 (2013) - [c31]Mathias Niepert:
Symmetry-Aware Marginal Density Estimation. AAAI 2013: 725-731 - [c30]Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt:
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models. AAAI 2013: 739-745 - [c29]Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt:
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models. StarAI@AAAI 2013 - [c28]Daniel Fleischhacker, Christian Meilicke, Johanna Völker, Mathias Niepert:
Computing Incoherence Explanations for Learned Ontologies. RR 2013: 80-94 - [c27]Mathias Niepert:
Statistical Relational Data Integration for Information Extraction. Reasoning Web 2013: 251-283 - [c26]Arnab Dutta, Christian Meilicke, Mathias Niepert, Simone Paolo Ponzetto:
Integrating Open and Closed Information Extraction: Challenges and First Steps. NLP-DBPEDIA@ISWC 2013 - [e2]Johanna Völker, Heiko Paulheim, Jens Lehmann, Mathias Niepert, Harald Sack:
Proceedings of the Second International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data, Montpellier, France, May 26, 2013. CEUR Workshop Proceedings 992, CEUR-WS.org 2013 [contents] - [i6]Mathias Niepert:
Symmetry-Aware Marginal Density Estimation. CoRR abs/1304.2694 (2013) - [i5]Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt:
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models. CoRR abs/1304.4379 (2013) - 2012
- [c25]Henrik Leopold, Mathias Niepert, Matthias Weidlich, Jan Mendling, Remco M. Dijkman, Heiner Stuckenschmidt:
Probabilistic Optimization of Semantic Process Model Matching. BPM 2012: 319-334 - [c24]Mathias Niepert, Christian Meilicke, Heiner Stuckenschmidt:
Towards Distributed MCMC Inference in Probabilistic Knowledge Bases. AKBC-WEKEX@NAACL-HLT 2012: 1-6 - [c23]Mathias Niepert:
Lifted Probabilistic Inference: An MCMC Perspective. StarAI@UAI 2012 - [c22]Mathias Niepert:
Markov Chains on Orbits of Permutation Groups. UAI 2012: 624-633 - [e1]Johanna Völker, Heiko Paulheim, Jens Lehmann, Mathias Niepert:
Proceedings of the First International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data, Heraklion, Greece, May 27, 2012. CEUR Workshop Proceedings 868, CEUR-WS.org 2012 [contents] - [i4]Mathias Niepert:
A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks. CoRR abs/1203.3499 (2012) - [i3]Mathias Niepert:
Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence. CoRR abs/1205.2621 (2012) - [i2]Mathias Niepert:
Markov Chains on Orbits of Permutation Groups. CoRR abs/1206.5396 (2012) - 2011
- [j6]Rim Helaoui, Mathias Niepert, Heiner Stuckenschmidt:
Recognizing interleaved and concurrent activities using qualitative and quantitative temporal relationships. Pervasive Mob. Comput. 7(6): 660-670 (2011) - [j5]Cameron Buckner, Mathias Niepert, Colin Allen:
From encyclopedia to ontology: toward dynamic representation of the discipline of philosophy. Synth. 182(2): 205-233 (2011) - [c21]Johanna Völker, Mathias Niepert:
Statistical Schema Induction. ESWC (1) 2011: 124-138 - [c20]Mathias Niepert, Jan Noessner, Heiner Stuckenschmidt:
Log-Linear Description Logics. IJCAI 2011: 2153-2158 - [c19]Cäcilia Zirn, Mathias Niepert, Heiner Stuckenschmidt, Michael Strube:
Fine-Grained Sentiment Analysis with Structural Features. IJCNLP 2011: 336-344 - [c18]Rim Helaoui, Mathias Niepert, Heiner Stuckenschmidt:
Recognizing interleaved and concurrent activities: A statistical-relational approach. PerCom 2011: 1-9 - [c17]Jan Noessner, Mathias Niepert:
ELOG: A Probabilistic Reasoner for OWL EL. RR 2011: 281-286 - [c16]Mathias Niepert, Jan Noessner, Christian Meilicke, Heiner Stuckenschmidt:
Probabilistic-Logical Web Data Integration. Reasoning Web 2011: 504-533 - [c15]Mathias Niepert:
Reasoning under Uncertainty with Log-Linear Description Logics. URSW 2011: 105-108 - [c14]Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt:
Coherent Top-k Ontology Alignment for OWL EL. SUM 2011: 415-427 - 2010
- [j4]Mathias Niepert, Dirk Van Gucht, Marc Gyssens:
Logical and algorithmic properties of stable conditional independence. Int. J. Approx. Reason. 51(5): 531-543 (2010) - [j3]Mathias Niepert:
"Towards Collaboratively Learning and Populating Ontologies for the Social-Semantic Web" by Mathias Niepert, with Jessica Rubart as coordinator. SIGWEB Newsl. 2010(Spring): 3:1-3:4 (2010) - [c13]Mathias Niepert, Christian Meilicke, Heiner Stuckenschmidt:
A Probabilistic-Logical Framework for Ontology Matching. AAAI 2010: 1413-1418 - [c12]Jan Noessner, Mathias Niepert, Christian Meilicke, Heiner Stuckenschmidt:
Leveraging Terminological Structure for Object Reconciliation. ESWC (2) 2010: 334-348 - [c11]Robert Meusel, Mathias Niepert, Kai Eckert, Heiner Stuckenschmidt:
Thesaurus Extension Using Web Search Engines. ICADL 2010: 198-207 - [c10]Rim Helaoui, Mathias Niepert, Heiner Stuckenschmidt:
A Statistical-Relational Activity Recognition Framework for Ambient Assisted Living Systems. ISAmI 2010: 247-254 - [c9]Kai Eckert, Mathias Niepert, Christof Niemann, Cameron Buckner, Colin Allen, Heiner Stuckenschmidt:
Crowdsourcing the assembly of concept hierarchies. JCDL 2010: 139-148 - [c8]Jan Noessner, Mathias Niepert:
CODI: Combinatorial Optimization for Data Integration: results for OAEI 2010. OM 2010 - [c7]Nikolas Schmitt, Mathias Niepert, Heiner Stuckenschmidt:
BRAMBLE: A Web-based Framework for Interactive RDF-Graph Visualisation. ISWC (Posters & Demos) 2010 - [c6]Mathias Niepert:
A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks. UAI 2010: 384-391
2000 – 2009
- 2009
- [j2]Mathias Niepert, Cameron Buckner, Jaimie Murdock, Colin Allen:
InPhO: A System for Collaboratively Populating and Extending a Dynamic Ontology. Bull. IEEE Tech. Comm. Digit. Libr. 5(1) (2009) - [c5]Mathias Niepert:
Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence. UAI 2009: 428-435 - 2008
- [j1]Colin Allen, Cameron Buckner, Mathias Niepert:
The World is Not Flat: Expertise and InPhO. First Monday 13(8) (2008) - [c4]Mathias Niepert, Cameron Buckner, Colin Allen:
Answer Set Programming on Expert Feedback to Populate and Extend Dynamic Ontologies. FLAIRS 2008: 500-505 - [c3]Mathias Niepert, Cameron Buckner, Jaimie Murdock, Colin Allen:
InPhO: a system for collaboratively populating and extending a dynamic ontology. JCDL 2008: 429 - [c2]Mathias Niepert, Dirk Van Gucht, Marc Gyssens:
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach. UAI 2008: 435-443 - [i1]Mathias Niepert, Dirk Van Gucht, Marc Gyssens:
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach. CoRR abs/0810.5717 (2008) - 2007
- [c1]Mathias Niepert, Cameron Buckner, Colin Allen:
A dynamic ontology for a dynamic reference work. JCDL 2007: 288-297
Coauthor Index
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