Max Welling

papers

2,594

total citations

papers (29)

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

NEURIPS 2023arXiv

citations

Rotating Features for Object Discovery

NEURIPS 2023arXiv

citations

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers

ICLR 2024arXiv

citations

The Convolution Exponential and Generalized Sylvester Flows

NEURIPS 2020arXiv

citations

Artificial Kuramoto Oscillatory Neurons

ICLR 2025arXiv

citations

Traveling Waves Encode The Recent Past and Enhance Sequence Learning

ICLR 2024arXiv

citations

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation

NEURIPS 2023arXiv

citations

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel

NEURIPS 2022arXiv

citations

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

ICML 2025arXiv

citations

Alleviating Adversarial Attacks on Variational Autoencoders with MCMC

NEURIPS 2022arXiv

citations

Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent

NEURIPS 2021arXiv

citations

Controlled Generation with Equivariant Variational Flow Matching

ICML 2025arXiv

citations

Flow Factorized Representation Learning

NEURIPS 2023arXiv

citations

Protect Your Score: Contact-Tracing with Differential Privacy Guarantees

AAAI 2024arXiv

citations

BARNN: A Bayesian Autoregressive and Recurrent Neural Network

ICML 2025arXiv

citations

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane

NEURIPS 2022

citations

Modality-Agnostic Topology Aware Localization

NEURIPS 2021

citations

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows

NEURIPS 2020arXiv

citations

Lie Point Symmetry and Physics-Informed Networks

NEURIPS 2023

citations

Max Welling

papers (29)

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

E(n) Equivariant Normalizing Flows

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

Bayesian Bits: Unifying Quantization and Pruning

Guided Variational Autoencoder for Disentanglement Learning

Experimental design for MRI by greedy policy search

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Natural Graph Networks

Topographic VAEs learn Equivariant Capsules

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

Rotating Features for Object Discovery

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers

The Convolution Exponential and Generalized Sylvester Flows

Artificial Kuramoto Oscillatory Neurons

Traveling Waves Encode The Recent Past and Enhance Sequence Learning

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

Alleviating Adversarial Attacks on Variational Autoencoders with MCMC

Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent

Controlled Generation with Equivariant Variational Flow Matching

Flow Factorized Representation Learning

Protect Your Score: Contact-Tracing with Differential Privacy Guarantees

BARNN: A Bayesian Autoregressive and Recurrent Neural Network

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane

Modality-Agnostic Topology Aware Localization

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows

Lie Point Symmetry and Physics-Informed Networks

papers (29)

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

E(n) Equivariant Normalizing Flows

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

Bayesian Bits: Unifying Quantization and Pruning

Guided Variational Autoencoder for Disentanglement Learning

Experimental design for MRI by greedy policy search

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Natural Graph Networks

Topographic VAEs learn Equivariant Capsules

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

Rotating Features for Object Discovery

GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers

The Convolution Exponential and Generalized Sylvester Flows

Artificial Kuramoto Oscillatory Neurons

Traveling Waves Encode The Recent Past and Enhance Sequence Learning

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

Alleviating Adversarial Attacks on Variational Autoencoders with MCMC

Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent

Controlled Generation with Equivariant Variational Flow Matching

Flow Factorized Representation Learning

Protect Your Score: Contact-Tracing with Differential Privacy Guarantees

BARNN: A Bayesian Autoregressive and Recurrent Neural Network

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane

Modality-Agnostic Topology Aware Localization

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows

Lie Point Symmetry and Physics-Informed Networks