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ORCIDMax Welling
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- affiliation: University of Amsterdam, Informatics Institute, The Netherlands
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2020 – today
- 2024
[j37]Ilia Igashov
, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-conditional diffusion model for molecular linker design. Nat. Mac. Intell. 6(4): 417-427 (2024)- [j36]Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based drug design with equivariant diffusion models. Nat. Comput. Sci. 4(12): 899-909 (2024) - [c206]Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling:
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees. AAAI 2024: 14829-14837 - [c205]T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling:
Traveling Waves Encode The Recent Past and Enhance Sequence Learning. ICLR 2024 - [c204]Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger:
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. ICLR 2024 - [c203]Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang:
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML 2024 - [i186]Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang:
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR abs/2402.00809 (2024) - [i185]Sindy Löwe, Francesco Locatello, Max Welling:
Binding Dynamics in Rotating Features. CoRR abs/2402.05627 (2024) - [i184]Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling:
DNA: Differentially private Neural Augmentation for contact tracing. CoRR abs/2404.13381 (2024) - [i183]Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Anna Vaughan, Jayesh K. Gupta, Kit Thambiratnam, Alex Archibald, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris:
Aurora: A Foundation Model of the Atmosphere. CoRR abs/2405.13063 (2024) - [i182]Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent:
Variational Flow Matching for Graph Generation. CoRR abs/2406.04843 (2024) - [i181]T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling:
A Spacetime Perspective on Dynamical Computation in Neural Information Processing Systems. CoRR abs/2409.13669 (2024) - [i180]Mathis Gerdes, Max Welling, Miranda C. N. Cheng:
GUD: Generation with Unified Diffusion. CoRR abs/2410.02667 (2024) - [i179]Yue Song, T. Anderson Keller, Yisong Yue, Pietro Perona, Max Welling:
Unsupervised Representation Learning from Sparse Transformation Analysis. CoRR abs/2410.05564 (2024) - [i178]Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling:
Artificial Kuramoto Oscillatory Neurons. CoRR abs/2410.13821 (2024) - 2023
- [j35]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [c202]Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling:
No time to waste: practical statistical contact tracing with few low-bit messages. AISTATS 2023: 7943-7960 - [c201]Winfried van den Dool, Tijmen Blankevoort, Max Welling, Yuki M. Asano:
Efficient Neural PDE-Solvers using Quantization Aware Training. ICCV (Workshops) 2023: 1415-1424 - [c200]Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta:
Clifford Neural Layers for PDE Modeling. ICLR 2023 - [c199]T. Anderson Keller, Max Welling:
Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks. ICML 2023: 16168-16189 - [c198]David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter:
Geometric Clifford Algebra Networks. ICML 2023: 29306-29337 - [c197]Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling:
Latent Traversals in Generative Models as Potential Flows. ICML 2023: 32288-32303 - [c196]Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh:
Lie Point Symmetry and Physics-Informed Networks. NeurIPS 2023 - [c195]Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling:
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. NeurIPS 2023 - [c194]Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling:
Rotating Features for Object Discovery. NeurIPS 2023 - [c193]Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani:
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. NeurIPS 2023 - [c192]Yue Song, Andy Keller, Nicu Sebe, Max Welling:
Flow Factorized Representation Learning. NeurIPS 2023 - [c191]Tim Bakker, Herke van Hoof, Max Welling:
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) 2023: 3-19 - [i177]Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling:
Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines. CoRR abs/2301.04168 (2023) - [i176]David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter:
Geometric Clifford Algebra Networks. CoRR abs/2302.06594 (2023) - [i175]Evgenii Egorov, Roberto Bondesan, Max Welling:
The END: An Equivariant Neural Decoder for Quantum Error Correction. CoRR abs/2304.07362 (2023) - [i174]Yue Song, Andy Keller, Nicu Sebe, Max Welling:
Latent Traversals in Generative Models as Potential Flows. CoRR abs/2304.12944 (2023) - [i173]Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling:
Rotating Features for Object Discovery. CoRR abs/2306.00600 (2023) - [i172]Kirill Neklyudov, Jannes Nys, Luca A. Thiede, Juan Carrasquilla, Qiang Liu, Max Welling, Alireza Makhzani:
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation. CoRR abs/2307.07050 (2023) - [i171]Winfried van den Dool, Tijmen Blankevoort, Max Welling, Yuki M. Asano:
Efficient Neural PDE-Solvers using Quantization Aware Training. CoRR abs/2308.07350 (2023) - [i170]Tim Bakker, Herke van Hoof, Max Welling:
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. CoRR abs/2309.05477 (2023) - [i169]T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling:
Traveling Waves Encode the Recent Past and Enhance Sequence Learning. CoRR abs/2309.08045 (2023) - [i168]Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling:
Flow Factorized Representation Learning. CoRR abs/2309.13167 (2023) - [i167]Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger:
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. CoRR abs/2310.10375 (2023) - [i166]Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh:
Lie Point Symmetry and Physics Informed Networks. CoRR abs/2311.04293 (2023) - [i165]Luisa H. B. Liboni, Roberto C. Budzinski, Alexandra N. Busch, Sindy Löwe, Thomas A. Keller, Max Welling, Lyle E. Muller:
Image segmentation with traveling waves in an exactly solvable recurrent neural network. CoRR abs/2311.16943 (2023) - [i164]Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson:
Perspectives on the State and Future of Deep Learning - 2023. CoRR abs/2312.09323 (2023) - [i163]Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling:
Protect Your Score: Contact Tracing With Differential Privacy Guarantees. CoRR abs/2312.11581 (2023) - 2022
- [j34]Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling:
Complex-Valued Autoencoders for Object Discovery. Trans. Mach. Learn. Res. 2022 (2022) - [c190]Zhuo Su, Max Welling, Matti Pietikäinen, Li Liu:
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation. 3DV 2022: 547-556 - [c189]Kirill Neklyudov, Max Welling:
Orbital MCMC. AISTATS 2022: 5790-5814 - [c188]Sindy Löwe, David Madras, Richard S. Zemel, Max Welling:
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data. CLeaR 2022: 509-525 - [c187]Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling:
Deep Policy Dynamic Programming for Vehicle Routing Problems. CPAIOR 2022: 190-213 - [c186]Shreya Kadambi, Arash Behboodi, Joseph B. Soriaga, Max Welling, Roohollah Amiri, Srinivas Yerramalli, Taesang Yoo:
Neural RF SLAM for unsupervised positioning and mapping with channel state information. ICC 2022: 3238-3244 - [c185]Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling:
Geometric and Physical Quantities improve E(3) Equivariant Message Passing. ICLR 2022 - [c184]Johannes Brandstetter, Daniel E. Worrall, Max Welling:
Message Passing Neural PDE Solvers. ICLR 2022 - [c183]Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling:
Multi-Agent MDP Homomorphic Networks. ICLR 2022 - [c182]Johannes Brandstetter, Max Welling, Daniel E. Worrall:
Lie Point Symmetry Data Augmentation for Neural PDE Solvers. ICML 2022: 2241-2256 - [c181]Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling:
Equivariant Diffusion for Molecule Generation in 3D. ICML 2022: 8867-8887 - [c180]Gabriele Cesa, Arash Behboodi, Taco S. Cohen, Max Welling:
On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane. NeurIPS 2022 - [c179]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. NeurIPS 2022 - [c178]ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling:
Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel. NeurIPS 2022 - [i162]Johannes Brandstetter, Daniel E. Worrall, Max Welling:
Message Passing Neural PDE Solvers. CoRR abs/2202.03376 (2022) - [i161]Johannes Brandstetter, Max Welling, Daniel E. Worrall:
Lie Point Symmetry Data Augmentation for Neural PDE Solvers. CoRR abs/2202.07643 (2022) - [i160]Shreya Kadambi, Arash Behboodi, Joseph B. Soriaga, Max Welling, Roohollah Amiri, Srinivas Yerramalli, Taesang Yoo:
Neural RF SLAM for unsupervised positioning and mapping with channel state information. CoRR abs/2203.08264 (2022) - [i159]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Defending Variational Autoencoders from Adversarial Attacks with MCMC. CoRR abs/2203.09940 (2022) - [i158]Shi Hu, Eric T. Nalisnick, Max Welling:
Adversarial Defense via Image Denoising with Chaotic Encryption. CoRR abs/2203.10290 (2022) - [i157]Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling:
Equivariant Diffusion for Molecule Generation in 3D. CoRR abs/2203.17003 (2022) - [i156]Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling:
Complex-Valued Autoencoders for Object Discovery. CoRR abs/2204.02075 (2022) - [i155]Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling:
Path Integral Stochastic Optimal Control for Sampling Transition Paths. CoRR abs/2207.02149 (2022) - [i154]ChangYong Oh, Roberto Bondesan, Dana Kianfar, Rehan Ahmed, Rishubh Khurana, Payal Agarwal, Romain Lepert, Mysore Sriram, Max Welling:
Bayesian Optimization for Macro Placement. CoRR abs/2207.08398 (2022) - [i153]Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta:
Clifford Neural Layers for PDE Modeling. CoRR abs/2209.04934 (2022) - [i152]Zhuo Su, Max Welling, Matti Pietikäinen, Li Liu:
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation. CoRR abs/2209.05924 (2022) - [i151]Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design. CoRR abs/2210.05274 (2022) - [i150]Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based Drug Design with Equivariant Diffusion Models. CoRR abs/2210.13695 (2022) - [i149]Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling:
Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports 12(4): 13-25 (2022) - [i148]David Duvenaud, Markus Heinonen, Michael Tiemann, Max Welling:
Differential Equations and Continuous-Time Deep Learning (Dagstuhl Seminar 22332). Dagstuhl Reports 12(8): 20-30 (2022) - 2021
- [j33]Kumar Pratik, Bhaskar D. Rao, Max Welling:
RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection. IEEE Trans. Signal Process. 69: 459-473 (2021) - [c177]Victor Garcia Satorras, Max Welling:
Neural Enhanced Belief Propagation on Factor Graphs. AISTATS 2021: 685-693 - [c176]Priyank Jaini, Didrik Nielsen, Max Welling:
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. AISTATS 2021: 3349-3357 - [c175]Kumar Pratik, Rana Ali Amjad, Arash Behboodi, Joseph B. Soriaga, Max Welling:
Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking. GLOBECOM 2021: 1-6 - [c174]T. Anderson Keller, Max Welling:
Predictive Coding with Topographic Variational Autoencoders. ICCVW 2021: 1086-1091 - [c173]Marc Anton Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. ICLR 2021 - [c172]Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling:
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR 2021 - [c171]Roberto Bondesan, Max Welling:
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. ICML 2021: 1038-1048 - [c170]Marc Finzi, Max Welling, Andrew Gordon Wilson:
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. ICML 2021: 3318-3328 - [c169]Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling:
Federated Learning of User Verification Models Without Sharing Embeddings. ICML 2021: 4328-4336 - [c168]T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling:
Self Normalizing Flows. ICML 2021: 5378-5387 - [c167]Victor Garcia Satorras, Emiel Hoogeboom, Max Welling:
E(n) Equivariant Graph Neural Networks. ICML 2021: 9323-9332 - [c166]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - [c165]Shi Hu, Nicola Pezzotti, Max Welling:
Learning to Predict Error for MRI Reconstruction. MICCAI (3) 2021: 604-613 - [c164]Victor Garcia Satorras, Emiel Hoogeboom, Fabian Fuchs, Ingmar Posner, Max Welling:
E(n) Equivariant Normalizing Flows. NeurIPS 2021: 4181-4192 - [c163]Farhad Ghazvinian Zanjani, Ilia Karmanov, Hanno Ackermann, Daniel Dijkman, Simone Merlin, Max Welling, Fatih Porikli:
Modality-Agnostic Topology Aware Localization. NeurIPS 2021: 10457-10468 - [c162]Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling:
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions. NeurIPS 2021: 12454-12465 - [c161]Priyank Jaini, Lars Holdijk, Max Welling:
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. NeurIPS 2021: 16727-16737 - [c160]T. Anderson Keller, Max Welling:
Topographic VAEs learn Equivariant Capsules. NeurIPS 2021: 28585-28597 - [c159]Shi Hu, Egill A. Fridgeirsson, Guido van Wingen, Max Welling:
Transformer-Based Deep Survival Analysis. SPACA 2021: 132-148 - [c158]ChangYong Oh, Efstratios Gavves, Max Welling:
Mixed variable Bayesian optimization with frequency modulated kernels. UAI 2021: 950-960 - [i147]Priyank Jaini, Didrik Nielsen, Max Welling:
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. CoRR abs/2102.02374 (2021) - [i146]Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling:
Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models. CoRR abs/2102.05379 (2021) - [i145]Victor Garcia Satorras, Emiel Hoogeboom, Max Welling:
E(n) Equivariant Graph Neural Networks. CoRR abs/2102.09844 (2021) - [i144]Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling:
Deep Policy Dynamic Programming for Vehicle Routing Problems. CoRR abs/2102.11756 (2021) - [i143]ChangYong Oh, Efstratios Gavves, Max Welling:
Mixed Variable Bayesian Optimization with Frequency Modulated Kernels. CoRR abs/2102.12792 (2021) - [i142]ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling:
Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels. CoRR abs/2102.13382 (2021) - [i141]Maximilian Ilse, Patrick Forré, Max Welling, Joris M. Mooij:
Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions. CoRR abs/2103.04786 (2021) - [i140]Roberto Bondesan, Max Welling:
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. CoRR abs/2103.04913 (2021) - [i139]Anna Kuzina, Max Welling, Jakub M. Tomczak:
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks. CoRR abs/2103.06701 (2021) - [i138]Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling:
Federated Learning of User Verification Models Without Sharing Embeddings. CoRR abs/2104.08776 (2021) - [i137]Marc Finzi, Max Welling, Andrew Gordon Wilson:
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. CoRR abs/2104.09459 (2021) - [i136]Victor Garcia Satorras, Emiel Hoogeboom, Fabian B. Fuchs, Ingmar Posner, Max Welling:
E(n) Equivariant Normalizing Flows for Molecule Generation in 3D. CoRR abs/2105.09016 (2021) - [i135]Maurice Weiler, Patrick Forré, Erik Verlinde, Max Welling:
Coordinate Independent Convolutional Networks - Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds. CoRR abs/2106.06020 (2021) - [i134]Priyank Jaini, Lars Holdijk, Max Welling:
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent. CoRR abs/2106.07832 (2021) - [i133]Kirill Neklyudov, Roberto Bondesan, Max Welling:
Deterministic Gibbs Sampling via Ordinary Differential Equations. CoRR abs/2106.10188 (2021) - [i132]Matthias Reisser, Christos Louizos, Efstratios Gavves, Max Welling:
Federated Mixture of Experts. CoRR abs/2107.06724 (2021) - [i131]T. Anderson Keller, Max Welling:
Topographic VAEs learn Equivariant Capsules. CoRR abs/2109.01394 (2021) - [i130]Kumar Pratik, Rana Ali Amjad, Arash Behboodi, Joseph B. Soriaga, Max Welling:
Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking. CoRR abs/2109.12561 (2021) - [i129]Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling:
Geometric and Physical Quantities improve E(3) Equivariant Message Passing. CoRR abs/2110.02905 (2021) - [i128]Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling:
Multi-Agent MDP Homomorphic Networks. CoRR abs/2110.04495 (2021) - [i127]T. Anderson Keller, Qinghe Gao, Max Welling:
Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders. CoRR abs/2110.13911 (2021) - [i126]Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling:
An Expectation-Maximization Perspective on Federated Learning. CoRR abs/2111.10192 (2021) - [i125]Kirill Neklyudov, Priyank Jaini, Max Welling:
Particle Dynamics for Learning EBMs. CoRR abs/2111.13772 (2021) - 2020
- [j32]