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ORCIDMax Welling
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- affiliation: University of Amsterdam, Informatics Institute, The Netherlands
- affiliation: University of California, Irvine, USA
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2020 – today
- 2023
[i166]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)- [i165]David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter:
Geometric Clifford Algebra Networks. CoRR abs/2302.06594 (2023) - [i164]Evgenii Egorov, Roberto Bondesan, Max Welling:
The END: An Equivariant Neural Decoder for Quantum Error Correction. CoRR abs/2304.07362 (2023) - [i163]Yue Song, Andy Keller, Nicu Sebe, Max Welling:
Latent Traversals in Generative Models as Potential Flows. CoRR abs/2304.12944 (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 Z. Shilling, 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]Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling:
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer 53(8): 18-28 (2020) - [j31]Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling:
Variational Bayes In Private Settings (VIPS). J. Artif. Intell. Res. 68: 109-157 (2020) - [j30]Wouter Kool, Herke van Hoof, Max Welling:
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement. J. Mach. Learn. Res. 21: 47:1-47:36 (2020) - [j29]Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio Garcia-Uceda Juarez, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Graph refinement based airway extraction using mean-field networks and graph neural networks. Medical Image Anal. 64: 101751 (2020) - [c157]Elise van der Pol, Thomas Kipf, Frans A. Oliehoek, Max Welling:
Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. AAMAS 2020: 1431-1439 - [c156]Xiahan Shi, Leonard Salewski, Martin Schiegg, Max Welling:
Relational Generalized Few-Shot Learning. BMVC 2020 - [c155]Zheng Ding, Yifan Xu, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, Zhuowen Tu:
Guided Variational Autoencoder for Disentanglement Learning. CVPR 2020: 7917-7926 - [c154]Wouter Kool, Herke van Hoof, Max Welling:
Estimating Gradients for Discrete Random Variables by Sampling without Replacement. ICLR 2020 - [c153]Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling:
Gradient $\ell_1$ Regularization for Quantization Robustness. ICLR 2020 - [c152]Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling:
Batch-shaping for learning conditional channel gated networks. ICLR 2020 - [c151]Thomas N. Kipf, Elise van der Pol, Max Welling:
Contrastive Learning of Structured World Models. ICLR 2020 - [c150]Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang:
To Relieve Your Headache of Training an MRF, Take AdVIL. ICLR 2020 - [c149]Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov:
Involutive MCMC: a Unifying Framework. ICML 2020: 7273-7282 - [c148]Max Welling:
Integrating Generative Modeling into Deep Learning. ICPRAM 2020: 9 - [c147]James R. Foulds, Mijung Park, Kamalika Chaudhuri, Max Welling:
Variational Bayes in Private Settings (VIPS) (Extended Abstract). IJCAI 2020: 5050-5054 - [c146]Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling:
DIVA: Domain Invariant Variational Autoencoders. MIDL 2020: 322-348 - [c145]Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling:
Bayesian Bits: Unifying Quantization and Pruning. NeurIPS 2020 - [c144]Tim Bakker, Herke van Hoof, Max Welling:
Experimental design for MRI by greedy policy search. NeurIPS 2020 - [c143]Fabian Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling:
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. NeurIPS 2020 - [c142]Pim de Haan, Taco S. Cohen, Max Welling:
Natural Graph Networks. NeurIPS 2020 - [c141]Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling:
The Convolution Exponential and Generalized Sylvester Flows. NeurIPS 2020 - [c140]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS 2020 - [c139]Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling:
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. NeurIPS 2020 - [i124]Shi Hu, Nicola Pezzotti, Dimitrios Mavroeidis, Max Welling:
Simple and Accurate Uncertainty Quantification from Bias-Variance Decomposition. CoRR abs/2002.05582 (2020) - [i123]Wouter Kool, Herke van Hoof, Max Welling:
Estimating Gradients for Discrete Random Variables by Sampling without Replacement. CoRR abs/2002.06043 (2020) - [i122]Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling:
Gradient 𝓁1 Regularization for Quantization Robustness. CoRR abs/2002.07520 (2020) - [i121]Elise van der Pol, Thomas N. Kipf, Frans A. Oliehoek, Max Welling:
Plannable Approximations to MDP Homomorphisms: Equivariance under Actions. CoRR abs/2002.11963 (2020) - [i120]Victor Garcia Satorras, Max Welling:
Neural Enhanced Belief Propagation on Factor Graphs. CoRR abs/2003.01998 (2020) - [i119]Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling:
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR abs/2003.05425 (2020) - [i118]Zheng Ding, Yifan Xu, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, Zhuowen Tu:
Guided Variational Autoencoder for Disentanglement Learning. CoRR abs/2004.01255 (2020) - [i117]Mirgahney Mohamed, Gabriele Cesa, Taco S. Cohen, Max Welling:
A Data and Compute Efficient Design for Limited-Resources Deep Learning. CoRR abs/2004.09691 (2020) - [i116]Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling:
Bayesian Bits: Unifying Quantization and Pruning. CoRR abs/2005.07093 (2020) - [i115]Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling:
The Convolution Exponential and Generalized Sylvester Flows. CoRR abs/2006.01910 (2020) - [i114]Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling:
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks. CoRR abs/2006.10503 (2020) - [i113]Sindy Löwe, David Madras, Richard S. Zemel, Max Welling:
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data. CoRR abs/2006.10833 (2020) - [i112]Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov:
Involutive MCMC: a Unifying Framework. CoRR abs/2006.16653 (2020) - [i111]Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling:
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning. CoRR abs/2006.16908 (2020) - [i110]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR abs/2007.02731 (2020) - [i109]Hossein Hosseini, Sungrack Yun, Hyunsin Park, Christos Louizos, Joseph Soriaga, Max Welling:
Federated Learning of User Authentication Models. CoRR abs/2007.04618 (2020) - [i108]Pim de Haan, Taco Cohen, Max Welling:
Natural Graph Networks. CoRR abs/2007.08349 (2020) - [i107]Kirill Neklyudov, Max Welling:
Orbital MCMC. CoRR abs/2010.08047 (2020) - [i106]Marc Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. CoRR abs/2010.10876 (2020) - [i105]Roberto Bondesan, Max Welling:
Quantum Deformed Neural Networks. CoRR abs/2010.11189 (2020) - [i104]Tim Bakker, Herke van Hoof, Max Welling:
Experimental design for MRI by greedy policy search. CoRR abs/2010.16262 (2020) - [i103]T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling:
Self Normalizing Flows. CoRR abs/2011.07248 (2020)
2010 – 2019
- 2019
- [j28]Diederik P. Kingma, Max Welling:
An Introduction to Variational Autoencoders. Found. Trends Mach. Learn. 12(4): 307-392 (2019) - [j27]Kai Lønning, Patrick Putzky, Jan-Jakob Sonke, Liesbeth Reneman, Matthan W. A. Caan, Max Welling:
Recurrent inference machines for reconstructing heterogeneous MRI data. Medical Image Anal. 53: 64-78 (2019) - [c138]Peter O'Connor, Efstratios Gavves, Max Welling:
Training a Spiking Neural Network with Equilibrium Propagation. AISTATS 2019: 1516-1523 - [c137]Markus Nagel, Mart van Baalen, Tijmen Blankevoort, Max Welling:
Data-Free Quantization Through Weight Equalization and Bias Correction. ICCV 2019: 1325-1334 - [c136]