Max Welling
Identifiers
- name variant Max Welling 0.60 · backfill
Papers (100)
- Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models cs.LG · 2026 · author #2
- Flowing with Confidence stat.ML · 2026 · author #3
- Spontaneous symmetry breaking and Goldstone modes for deep information propagation cs.LG · 2026 · author #5
- Kernel-Gradient Drifting Models cs.LG · 2026 · author #3
- BaLoRA: Bayesian Low-Rank Adaptation of Large Scale Models cs.LG · 2026 · author #3
- (Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models cs.LG · 2026 · author #3
- Krause Synchronization Transformers cs.LG · 2026 · author #3
- Differentiable probabilistic models of scientific imaging with the Fourier slice theorem cs.LG · 2019 · author #5
- Covariance in Physics and Convolutional Neural Networks cs.LG · 2019 · author #6
- Deep Scale-spaces: Equivariance Over Scale cs.LG · 2019 · author #2
- Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement cs.LG · 2019 · author #3
- Gauge Equivariant Convolutional Networks and the Icosahedral CNN cs.LG · 2019 · author #4
- Emerging Convolutions for Generative Normalizing Flows cs.LG · 2019 · author #3
- The Deep Weight Prior stat.ML · 2018 · author #5
- Predictive Uncertainty through Quantization cs.LG · 2018 · author #3
- Relaxed Quantization for Discretized Neural Networks cs.LG · 2018 · author #5
- Sinkhorn AutoEncoders cs.LG · 2018 · author #6
- Probabilistic Binary Neural Networks cs.LG · 2018 · author #2
- 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data cs.LG · 2018 · author #3
- Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks cs.CV · 2018 · author #5
- Rotation Equivariant CNNs for Digital Pathology cs.CV · 2018 · author #5
- Primal-Dual Wasserstein GAN stat.ML · 2018 · author #3
- Extraction of Airways using Graph Neural Networks cs.CV · 2018 · author #3
- Graphical Generative Adversarial Networks cs.LG · 2018 · author #2
- Mean Field Network based Graph Refinement with application to Airway Tree Extraction cs.CV · 2018 · author #2
- Attention, Learn to Solve Routing Problems! stat.ML · 2018 · author #3
- Sylvester Normalizing Flows for Variational Inference stat.ML · 2018 · author #4
- HexaConv cs.LG · 2018 · author #4
- Attention-based Deep Multiple Instance Learning cs.LG · 2018 · author #3
- Neural Relational Inference for Interacting Systems stat.ML · 2018 · author #4
- Spherical CNNs cs.LG · 2018 · author #4
- Learning Sparse Neural Networks through $L_0$ Regularization stat.ML · 2017 · author #2
- Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification cs.LG · 2017 · author #3
- Improved Bayesian Compression stat.ML · 2017 · author #3
- Convolutional Networks for Spherical Signals cs.LG · 2017 · author #4
- Temporally Efficient Deep Learning with Spikes cs.NE · 2017 · author #3
- Recurrent Inference Machines for Solving Inverse Problems cs.NE · 2017 · author #2
- Improving Variational Auto-Encoders using convex combination linear Inverse Autoregressive Flow stat.ML · 2017 · author #2
- Graph Convolutional Matrix Completion stat.ML · 2017 · author #3
- Causal Effect Inference with Deep Latent-Variable Models stat.ML · 2017 · author #6
- Bayesian Compression for Deep Learning stat.ML · 2017 · author #3
- VAE with a VampPrior cs.LG · 2017 · author #2
- Modeling Relational Data with Graph Convolutional Networks stat.ML · 2017 · author #6
- Multiplicative Normalizing Flows for Variational Bayesian Neural Networks stat.ML · 2017 · author #2
- Visualizing Deep Neural Network Decisions: Prediction Difference Analysis cs.CV · 2017 · author #4
- Soft Weight-Sharing for Neural Network Compression stat.ML · 2017 · author #3
- Steerable CNNs cs.LG · 2016 · author #2
- Improving Variational Auto-Encoders using Householder Flow cs.LG · 2016 · author #2
- Variational Graph Auto-Encoders stat.ML · 2016 · author #2
- Accelerating the BSM interpretation of LHC data with machine learning hep-ph · 2016 · author #6
- Sigma Delta Quantized Networks cs.NE · 2016 · author #2
- Variational Bayes In Private Settings (VIPS) stat.ML · 2016 · author #4
- Private Topic Modeling stat.ML · 2016 · author #4
- Semi-Supervised Classification with Graph Convolutional Networks cs.LG · 2016 · author #2
- Automatic Variational ABC stat.ML · 2016 · author #5
- Improving Variational Inference with Inverse Autoregressive Flow cs.LG · 2016 · author #6
- A note on privacy preserving iteratively reweighted least squares cs.CR · 2016 · author #2
- DP-EM: Differentially Private Expectation Maximization cs.LG · 2016 · author #4
- On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis cs.LG · 2016 · author #3
- Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors stat.ML · 2016 · author #2
- A New Method to Visualize Deep Neural Networks cs.CV · 2016 · author #3
- Deep Spiking Networks cs.NE · 2016 · author #2
- Group Equivariant Convolutional Networks cs.LG · 2016 · author #2
- Herding as a Learning System with Edge-of-Chaos Dynamics stat.ML · 2016 · author #2
- The Variational Fair Autoencoder stat.ML · 2015 · author #4
- Scalable MCMC for Mixed Membership Stochastic Blockmodels cs.LG · 2015 · author #3
- Bayesian Dark Knowledge cs.LG · 2015 · author #4
- Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference cs.LG · 2015 · author #2
- Variational Dropout and the Local Reparameterization Trick stat.ML · 2015 · author #3
- Harmonic Exponential Families on Manifolds stat.ML · 2015 · author #2
- Hamiltonian ABC stat.ML · 2015 · author #3
- Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC cs.LG · 2015 · author #5
- Transformation Properties of Learned Visual Representations cs.LG · 2014 · author #2
- POPE: Post Optimization Posterior Evaluation of Likelihood Free Models stat.ML · 2014 · author #6
- MLitB: Machine Learning in the Browser cs.DC · 2014 · author #5
- Markov Chain Monte Carlo and Variational Inference: Bridging the Gap stat.CO · 2014 · author #3
- Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior cs.LG · 2014 · author #2
- Semi-Supervised Learning with Deep Generative Models cs.LG · 2014 · author #4
- Exploiting the Statistics of Learning and Inference cs.LG · 2014 · author #1
- Learning the Irreducible Representations of Commutative Lie Groups cs.LG · 2014 · author #2
- Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets cs.LG · 2014 · author #2
- GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation cs.LG · 2014 · author #2
- Auto-Encoding Variational Bayes stat.ML · 2013 · author #2
- Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation cs.LG · 2013 · author #5
- Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget cs.LG · 2013 · author #3
- Herded Gibbs Sampling cs.LG · 2013 · author #6
- Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation cs.AI · 2013 · author #1
- Efficient Parametric Projection Pursuit Density Estimation cs.LG · 2012 · author #1
- A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation cs.AI · 2012 · author #1
- Generalized Belief Propagation on Tree Robust Structured Region Graphs cs.AI · 2012 · author #2
- Semisupervised Classifier Evaluation and Recalibration cs.LG · 2012 · author #2
- On the Choice of Regions for Generalized Belief Propagation cs.AI · 2012 · author #1
- Structured Region Graphs: Morphing EP into GBP cs.AI · 2012 · author #1
- Bayesian Random Fields: The Bethe-Laplace Approximation cs.LG · 2012 · author #1
- Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation stat.ME · 2012 · author #4
- Hybrid Variational/Gibbs Collapsed Inference in Topic Models cs.LG · 2012 · author #1
- Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior stat.ML · 2012 · author #2
- Herding Dynamic Weights for Partially Observed Random Field Models cs.LG · 2012 · author #1
- On Smoothing and Inference for Topic Models cs.LG · 2012 · author #2
- Super-Samples from Kernel Herding cs.LG · 2012 · author #2
Mentions
- 1511.00830 #4 · backfill · confidence 0.70 Max Welling
- 1510.04815 #3 · backfill · confidence 0.70 Max Welling
- 2606.04822 #2 · arxiv_oai · confidence 0.70 Max Welling
- 1506.04416 #4 · backfill · confidence 0.70 Max Welling
- 1506.03693 #2 · backfill · confidence 0.70 Max Welling
- 1506.02557 #3 · backfill · confidence 0.70 Max Welling
- 1505.04413 #2 · backfill · confidence 0.70 Max Welling
- 1503.01916 #3 · backfill · confidence 0.70 Max Welling
- 1503.01596 #5 · backfill · confidence 0.70 Max Welling
- 1412.7659 #2 · backfill · confidence 0.70 Max Welling
- 1412.3051 #6 · backfill · confidence 0.70 Max Welling
- 1412.2432 #5 · backfill · confidence 0.70 Max Welling
- 1410.6460 #3 · backfill · confidence 0.70 Max Welling
- 1408.2047 #2 · backfill · confidence 0.70 Max Welling
- 1406.5298 #4 · backfill · confidence 0.70 Max Welling
- 1402.7025 #1 · backfill · confidence 0.70 Max Welling
- 1402.4437 #2 · backfill · confidence 0.70 Max Welling
- 1402.0480 #2 · backfill · confidence 0.70 Max Welling
- 1401.2838 #2 · backfill · confidence 0.70 Max Welling
- 1312.6114 #2 · backfill · confidence 0.70 Max Welling
- 1305.2452 #5 · backfill · confidence 0.70 Max Welling
- 1304.5299 #3 · backfill · confidence 0.70 Max Welling
- 2602.11534 #3 · arxiv_oai · confidence 0.70 Max Welling
- 1301.4168 #6 · backfill · confidence 0.70 Max Welling
- 1301.2317 #1 · backfill · confidence 0.70 Max Welling
- 1212.2513 #1 · backfill · confidence 0.70 Max Welling
- 1210.4916 #1 · backfill · confidence 0.70 Max Welling
- 1210.4857 #2 · backfill · confidence 0.70 Max Welling
- 1210.2162 #2 · backfill · confidence 0.70 Max Welling
- 1207.4158 #1 · backfill · confidence 0.70 Max Welling
- 1207.1426 #1 · backfill · confidence 0.70 Max Welling
- 1206.6868 #1 · backfill · confidence 0.70 Max Welling
- 1206.6845 #4 · backfill · confidence 0.70 Max Welling
- 1206.3297 #1 · backfill · confidence 0.70 Max Welling
- 1206.1088 #2 · backfill · confidence 0.70 Max Welling
- 1205.2662 #2 · backfill · confidence 0.70 Max Welling
- 1205.2605 #1 · backfill · confidence 0.70 Max Welling
- 1203.3472 #2 · backfill · confidence 0.70 Max Welling
- 2605.18472 #3 · arxiv_oai · confidence 0.70 Max Welling
- 2604.16429 #3 · arxiv_oai · confidence 0.70 Max Welling
Frequent Coauthors
- Taco S. Cohen 10 shared papers
- Christos Louizos 7 shared papers
- Edward Meeds 7 shared papers
- Rianne van den Berg 7 shared papers
- Diederik P. Kingma 6 shared papers
- Jakub M. Tomczak 6 shared papers
- Yutian Chen 6 shared papers
- James Foulds 4 shared papers
- Kamalika Chaudhuri 4 shared papers
- Karen Ullrich 4 shared papers
- Mijung Park 4 shared papers
- Taco Cohen 4 shared papers
- Thomas N. Kipf 4 shared papers
- Yee Whye Teh 4 shared papers
- Anoop Korattikara 3 shared papers
- Bastiaan S. Veeling 3 shared papers
- Mario Geiger 3 shared papers
- Maurice Weiler 3 shared papers
- Padhraic Smyth 3 shared papers
- Peter O'Connor 3 shared papers