Max Welling

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

E(n) Equivariant Graph Neural Networks.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Proceedings of the 38th International Conference on Machine Learning, 2021

Self Normalizing Flows.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Federated Learning of User Verification Models Without Sharing Embeddings.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups.

[BibT_eX]

[DOI]

Marc Finzi

Andrew Gordon Wilson

Proceedings of the 38th International Conference on Machine Learning, 2021

The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning.

[BibT_eX]

[DOI]

Roberto Bondesan

Proceedings of the 38th International Conference on Machine Learning, 2021

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Probabilistic Numeric Convolutional Neural Networks.

[BibT_eX]

[DOI]

Marc Anton Finzi

Roberto Bondesan

Proceedings of the 9th International Conference on Learning Representations, 2021

Predictive Coding with Topographic Variational Autoencoders.

[BibT_eX]

[DOI]

T. Anderson Keller

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

Neural Enhanced Belief Propagation on Factor Graphs.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC.

[BibT_eX]

[DOI]

Priyank Jaini

Didrik Nielsen

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Graph refinement based airway extraction using mean-field networks and graph neural networks.

[BibT_eX]

[DOI]

Thomas Kipf

Antonio Garcia-Uceda Juarez

Medical Image Anal., 2020

Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Variational Bayes In Private Settings (VIPS).

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2020

Quantum Deformed Neural Networks.

[BibT_eX]

[DOI]

Roberto Bondesan

CoRR, 2020

Federated Learning of User Authentication Models.

[BibT_eX]

[DOI]

CoRR, 2020

A Data and Compute Efficient Design for Limited-Resources Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Gradient 𝓁1 Regularization for Quantization Robustness.

[BibT_eX]

[DOI]

CoRR, 2020

Simple and Accurate Uncertainty Quantification from Bias-Variance Decomposition.

[BibT_eX]

[DOI]

CoRR, 2020

A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence.

[BibT_eX]

[DOI]

Computer, 2020

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Convolution Exponential and Generalized Sylvester Flows.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Natural Graph Networks.

[BibT_eX]

[DOI]

Pim de Haan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Experimental design for MRI by greedy policy search.

[BibT_eX]

[DOI]

Tim Bakker

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bayesian Bits: Unifying Quantization and Pruning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DIVA: Domain Invariant Variational Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Variational Bayes in Private Settings (VIPS) (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Integrating Generative Modeling into Deep Learning.

[BibT_eX]

Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

Involutive MCMC: a Unifying Framework.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

To Relieve Your Headache of Training an MRF, Take AdVIL.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Contrastive Learning of Structured World Models.

[BibT_eX]

[DOI]

Elise van der Pol

Proceedings of the 8th International Conference on Learning Representations, 2020

Batch-shaping for learning conditional channel gated networks.

[BibT_eX]

[DOI]

Babak Ehteshami Bejnordi

Tijmen Blankevoort

Proceedings of the 8th International Conference on Learning Representations, 2020

Gradient $\ell_1$ Regularization for Quantization Robustness.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Estimating Gradients for Discrete Random Variables by Sampling without Replacement.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Guided Variational Autoencoder for Disentanglement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Relational Generalized Few-Shot Learning.

[BibT_eX]

[DOI]

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Recurrent inference machines for reconstructing heterogeneous MRI data.

[BibT_eX]

[DOI]

Medical Image Anal., 2019

An Introduction to Variational Autoencoders.

[BibT_eX]

[DOI]

Found. Trends Mach. Learn., 2019

Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Likelihoods with Conditional Normalizing Flows.

[BibT_eX]

[DOI]

CoRR, 2019

i-RIM applied to the fastMRI challenge.

[BibT_eX]

[DOI]

Patrick Putzky

Dimitrios Karkalousos

CoRR, 2019

DP-MAC: The Differentially Private Method of Auxiliary Coordinates for Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Relational Generalized Few-Shot Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Batch-Shaped Channel Gated Networks.

[BibT_eX]

[DOI]

Babak Ehteshami Bejnordi

Tijmen Blankevoort

CoRR, 2019

Covariance in Physics and Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Combinatorial Bayesian Optimization using Graph Representations.

[BibT_eX]

[DOI]

CoRR, 2019

Adversarial Variational Inference and Learning in Markov Random Fields.

[BibT_eX]

[DOI]

CoRR, 2019

Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Sinkhorn AutoEncoders.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Stochastic Activation Actor Critic Methods.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Deep Scale-spaces: Equivariance Over Scale.

[BibT_eX]

[DOI]

Daniel E. Worrall

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Combining Generative and Discriminative Models for Hybrid Inference.

[BibT_eX]

[DOI]

Zeynep Akata

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Invert to Learn to Invert.

[BibT_eX]

[DOI]

Patrick Putzky

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Combinatorial Bayesian Optimization using the Graph Cartesian Product.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Functional Neural Process.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Integer Discrete Flows and Lossless Compression.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Supervised Uncertainty Quantification for Segmentation with Multiple Annotations.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Emerging Convolutions for Generative Normalizing Flows.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Rianne van den Berg

Proceedings of the 36th International Conference on Machine Learning, 2019

Gauge Equivariant Convolutional Networks and the Icosahedral CNN.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Initialized Equilibrium Propagation for Backprop-Free Training.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Relaxed Quantization for Discretized Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Buy 4 REINFORCE Samples, Get a Baseline for Free!

[BibT_eX]

[DOI]

Proceedings of the Deep Reinforcement Learning Meets Structured Prediction, 2019

Attention, Learn to Solve Routing Problems!

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

DIVA: Domain Invariant Variational Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

The Deep Weight Prior.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Data-Free Quantization Through Weight Equalization and Bias Correction.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Training a Spiking Neural Network with Equilibrium Propagation.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models.

[BibT_eX]

[DOI]

CoRR, 2018

Predictive Uncertainty through Quantization.

[BibT_eX]

[DOI]

Bastiaan S. Veeling

Rianne van den Berg

CoRR, 2018

Probabilistic Binary Neural Networks.

[BibT_eX]

[DOI]

Jorn W. T. Peters

CoRR, 2018

Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Primal-Dual Wasserstein GAN.

[BibT_eX]

[DOI]

Mevlana Gemici

Zeynep Akata

CoRR, 2018

Extraction of Airways using Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Attention Solves Your TSP.

[BibT_eX]

[DOI]

CoRR, 2018

Sylvester Normalizing Flows for Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Graphical Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rotation Equivariant CNNs for Digital Pathology.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

BOCK : Bayesian Optimization with Cylindrical Kernels.

[BibT_eX]

[DOI]

ChangYong Oh

Proceedings of the 35th International Conference on Machine Learning, 2018

Neural Relational Inference for Interacting Systems.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Attention-based Deep Multiple Instance Learning.

[BibT_eX]

[DOI]

Maximilian Ilse

Proceedings of the 35th International Conference on Machine Learning, 2018

Temporally Efficient Deep Learning with Spikes.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Sparse Neural Networks through L_0 Regularization.

[BibT_eX]

[DOI]

Michael Sejr Schlichtkrull

Proceedings of the 6th International Conference on Learning Representations, 2018

HexaConv.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Spherical CNNs.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Modeling Relational Data with Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the Semantic Web - 15th International Conference, 2018

VAE with a VampPrior.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Learning Sparse Neural Networks through L0 Regularization.

[BibT_eX]

[DOI]

CoRR, 2017

Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification.

[BibT_eX]

[DOI]

Maximilian Ilse

CoRR, 2017

Convolutional Networks for Spherical Signals.

[BibT_eX]

[DOI]

CoRR, 2017

Recurrent Inference Machines for Solving Inverse Problems.

[BibT_eX]

[DOI]

Patrick Putzky

CoRR, 2017

Temporally Efficient Deep Learning with Spikes.

[BibT_eX]

[DOI]

CoRR, 2017

Graph Convolutional Matrix Completion.

[BibT_eX]

[DOI]

Rianne van den Berg

CoRR, 2017

Interpretation of microbiota-based diagnostics by explaining individual classifier decisions.

[BibT_eX]

[DOI]

BMC Bioinform., 2017

Bayesian Compression for Deep Learning.

[BibT_eX]

[DOI]

Karen Ullrich

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Causal Effect Inference with Deep Latent-Variable Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multiplicative Normalizing Flows for Variational Bayesian Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Soft Weight-Sharing for Neural Network Compression.

[BibT_eX]

[DOI]

Karen Ullrich

Proceedings of the 5th International Conference on Learning Representations, 2017

Sigma Delta Quantized Networks.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Semi-Supervised Classification with Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Steerable CNNs.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

DP-EM: Differentially Private Expectation Maximization.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Sequential Tests for Large-Scale Learning.

[BibT_eX]

[DOI]

Anoop Korattikara

Neural Comput., 2016

Herded Gibbs Sampling.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Marrying Graphical Models with Deep Learning.

[BibT_eX]

[DOI]

ERCIM News, 2016

A New Method to Visualize Deep Neural Networks.

[BibT_eX]

[DOI]

Luisa M. Zintgraf

CoRR, 2016

Improving Variational Auto-Encoders using Householder Flow.

[BibT_eX]

[DOI]

CoRR, 2016

A note on privacy preserving iteratively reweighted least squares.

[BibT_eX]

[DOI]

Mijung Park

CoRR, 2016

Private Topic Modeling.

[BibT_eX]

[DOI]

CoRR, 2016

Practical Privacy For Expectation Maximization.

[BibT_eX]

[DOI]

CoRR, 2016

Deep Spiking Networks.

[BibT_eX]

[DOI]

CoRR, 2016

The Variational Fair Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Variational Graph Auto-Encoders.

[BibT_eX]

[DOI]

CoRR, 2016

Improving Variational Inference with Inverse Autoregressive Flow.

[BibT_eX]

[DOI]

Tim Salimans

CoRR, 2016

Herding as a Learning System with Edge-of-Chaos Dynamics.

[BibT_eX]

[DOI]

CoRR, 2016

On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Improving Variational Autoencoders with Inverse Autoregressive Flow.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scalable Overlapping Community Detection.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Group Equivariant Convolutional Networks.

[BibT_eX]

[DOI]

Taco Cohen

Proceedings of the 33nd International Conference on Machine Learning, 2016

Scalable MCMC for Mixed Membership Stochastic Blockmodels.

[BibT_eX]

[DOI]

Wenzhe Li

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

MLitB: machine learning in the browser.

[BibT_eX]

[DOI]

PeerJ Comput. Sci., 2015

Transformation Properties of Learned Visual Representations.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Learning Representations, 2015

POPE: post optimization posterior evaluation of likelihood free models.

[BibT_eX]

[DOI]

BMC Bioinform., 2015

Hamiltonian ABC.

[BibT_eX]

[DOI]

Robert Leenders

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Variational Dropout and the Local Reparameterization Trick.

[BibT_eX]

[DOI]

Tim Salimans

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bayesian dark knowledge.

[BibT_eX]

[DOI]

Vivek Rathod

Kevin P. Murphy

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC.

[BibT_eX]

[DOI]

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Markov Chain Monte Carlo and Variational Inference: Bridging the Gap.

[BibT_eX]

[DOI]

Tim Salimans

Proceedings of the 32nd International Conference on Machine Learning, 2015

Harmonic Exponential Families on Manifolds.

[BibT_eX]

[DOI]

Taco Cohen

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Exploiting the Statistics of Learning and Inference.

[BibT_eX]

[DOI]

CoRR, 2014

Auto-Encoding Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Conference on Learning Representations, 2014

GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Semi-supervised Learning with Deep Generative Models.

[BibT_eX]

[DOI]

Shakir Mohamed

Danilo Jimenez Rezende

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Learning the Irreducible Representations of Commutative Lie Groups.

[BibT_eX]

[DOI]

Taco Cohen

Proceedings of the 31th International Conference on Machine Learning, 2014

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Distributed Stochastic Gradient MCMC.

[BibT_eX]

[DOI]

Babak Shahbaba

Proceedings of the 31th International Conference on Machine Learning, 2014

Approximate Slice Sampling for Bayesian Posterior Inference.

[BibT_eX]

[DOI]

Christopher DuBois

Padhraic Smyth

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation.

[BibT_eX]

[DOI]

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration.

[BibT_eX]

[DOI]

Peter Welinder

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Evidence Estimation for Bayesian Partially Observed MRFs.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

Distributed and Adaptive Darting Monte Carlo through Regenerations.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Predicting simulation parameters of biological systems using a Gaussian process model.

[BibT_eX]

[DOI]

Stat. Anal. Data Min., 2012

Editor's Note.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2012

State of the Journal.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2012

Scalable Inference on Kingman's Coalescent using Pair Similarity .

[BibT_eX]

[DOI]

Dilan Görür

Levi Boyles

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Semisupervised Classifier Evaluation and Recalibration

[BibT_eX]

[DOI]

Peter Welinder

CoRR, 2012

A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation.

[BibT_eX]

[DOI]

Andrew Gelfand

Alexander Ihler

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Generalized Belief Propagation on Tree Robust Structured Region Graphs.

[BibT_eX]

[DOI]

Andrew Gelfand

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

The Time-Marginalized Coalescent Prior for Hierarchical Clustering.

[BibT_eX]

[DOI]

Levi Boyles

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Exchangeable inconsistent priors for Bayesian posterior inference.

[BibT_eX]

[DOI]

Proceedings of the 2012 Information Theory and Applications Workshop, 2012

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Editor's Note.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Unsupervised Organization of Image Collections: Taxonomies and Beyond.

[BibT_eX]

[DOI]

Evgeniy Bart

IEEE Trans. Pattern Anal. Mach. Intell., 2011

Hidden-Unit Conditional Random Fields.

[BibT_eX]

[DOI]

Laurens van der Maaten

Lawrence K. Saul

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Statistical Optimization of Non-Negative Matrix Factorization.

[BibT_eX]

[DOI]

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Statistical Tests for Optimization Efficiency.

[BibT_eX]

[DOI]

Levi Boyles

Deva Ramanan

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Bayesian Learning via Stochastic Gradient Langevin Dynamics.

[BibT_eX]

[DOI]

Proceedings of the 28th International Conference on Machine Learning, 2011

Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2011

2010

Parametric Herding.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Localization Algorithms for Wireless Sensor Retrieval.

[BibT_eX]

[DOI]

Comput. J., 2010

Super-Samples from Kernel Herding.

[BibT_eX]

[DOI]

Alexander J. Smola

Proceedings of the UAI 2010, 2010

On Herding and the Perceptron Cycling Theorem.

[BibT_eX]

[DOI]

Andrew Gelfand

Laurens van der Maaten

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Dynamical Products of Experts for Modeling Financial Time Series.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures.

[BibT_eX]

[DOI]

Arthur U. Asuncion

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Bayesian k-Means as a "Maximization-Expectation" Algorithm.

[BibT_eX]

[DOI]

Neural Comput., 2009

Distributed Algorithms for Topic Models.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2009

Preface.

[BibT_eX]

[DOI]

David A. Van Dyk

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Herding Dynamic Weights for Partially Observed Random Field Models.

[BibT_eX]

[DOI]

Proceedings of the UAI 2009, 2009

On Smoothing and Inference for Topic Models.

[BibT_eX]

[DOI]

Proceedings of the UAI 2009, 2009

Base Station Localization in Search of Empty Spectrum Spaces in Cognitive Radio Networks.

[BibT_eX]

[DOI]

Proceedings of the MSN 2009, 2009

Bayesian Extreme Components Analysis.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2009, 2009

Herding dynamical weights to learn.

[BibT_eX]

[DOI]

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Hybrid Generative-Discriminative Visual Categorization.

[BibT_eX]

[DOI]

Alex Holub

Int. J. Comput. Vis., 2008

Hybrid Variational/Gibbs Collapsed Inference in Topic Models.

[BibT_eX]

[DOI]

Bert Kappen

Proceedings of the UAI 2008, 2008

Deterministic Latent Variable Models and Their Pitfalls.

[BibT_eX]

[DOI]

Chaitanya Chemudugunta

Nathan Sutter

Proceedings of the SIAM International Conference on Data Mining, 2008

Asynchronous Distributed Learning of Topic Models.

[BibT_eX]

[DOI]

Arthur U. Asuncion

Padhraic Smyth

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Fast collapsed gibbs sampling for latent dirichlet allocation.

[BibT_eX]

[DOI]

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Memory bounded inference in topic models.

[BibT_eX]

[DOI]

Ryan Gomes

Proceedings of the Machine Learning, 2008

Incremental learning of nonparametric Bayesian mixture models.

[BibT_eX]

[DOI]

Ryan Gomes

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

Unsupervised learning of visual taxonomies.

[BibT_eX]

[DOI]

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization.

[BibT_eX]

[DOI]

Evgeniy Bart

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

Product of experts.

[BibT_eX]

[DOI]

Scholarpedia, 2007

Generalized Darting Monte Carlo.

[BibT_eX]

[DOI]

Cristian Sminchisescu

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Infinite State Bayes-Nets for Structured Domains.

[BibT_eX]

[DOI]

Evgeniy Bart

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Collapsed Variational Inference for HDP.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Distributed Inference for Latent Dirichlet Allocation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Collapsed Variational Dirichlet Process Mixture Models.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2007, 2007

A Distributed Message Passing Algorithm for Sensor Localization.

[BibT_eX]

[DOI]

Joseph J. Lim

Proceedings of the Artificial Neural Networks, 2007

2006

Topographic Product Models Applied to Natural Scene Statistics.

[BibT_eX]

[DOI]

Simon Osindero

Neural Comput., 2006

Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation.

[BibT_eX]

[DOI]

Cogn. Sci., 2006

Bayesian Random Fields: The Bethe-Laplace Approximation.

[BibT_eX]

[DOI]

Sridevi Parise

Proceedings of the UAI '06, 2006

Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation.

[BibT_eX]

[DOI]

Proceedings of the UAI '06, 2006

Bayesian K-Means as a "Maximization-Expectation" Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation.

[BibT_eX]

[DOI]

David Newman

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Bayesian Model Scoring in Markov Random Fields.

[BibT_eX]

[DOI]

Sridevi Parise

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Accelerated Variational Dirichlet Process Mixtures.

[BibT_eX]

[DOI]

Nikos Vlassis

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

The rate adapting poisson model for information retrieval and object recognition.

[BibT_eX]

[DOI]

Peter V. Gehler

Alex Holub

Proceedings of the Machine Learning, 2006

2005

Structured Region Graphs: Morphing EP into GBP.

[BibT_eX]

[DOI]

Thomas P. Minka

Proceedings of the UAI '05, 2005

Products of Edge-perts.

[BibT_eX]

[DOI]

Peter V. Gehler

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Combining Generative Models and Fisher Kernels for Object Recognition.

[BibT_eX]

[DOI]

Alex Holub

Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV 2005), 2005

Learning in Markov Random Fields with Contrastive Free Energies.

[BibT_eX]

[DOI]

Charles Sutton

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Robust Higher Order Statistics.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Probabilistic sequential independent components analysis.

[BibT_eX]

[DOI]

Richard S. Zemel

IEEE Trans. Neural Networks, 2004

Linear Response Algorithms for Approximate Inference in Graphical Models.

[BibT_eX]

[DOI]

Neural Comput., 2004

On the Choice of Regions for Generalized Belief Propagation.

[BibT_eX]

[DOI]

Proceedings of the UAI '04, 2004

Exponential Family Harmoniums with an Application to Information Retrieval.

[BibT_eX]

[DOI]

Michal Rosen-Zvi

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Approximate inference by Markov chains on union spaces.

[BibT_eX]

[DOI]

Michal Rosen-Zvi

Proceedings of the Machine Learning, 2004

2003

Energy-Based Models for Sparse Overcomplete Representations.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Approximate inference in Boltzmann machines.

[BibT_eX]

[DOI]

Artif. Intell., 2003

Efficient Parametric Projection Pursuit Density Estimation.

[BibT_eX]

[DOI]

Richard S. Zemel

Proceedings of the UAI '03, 2003

Linear Response for Approximate Inference.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Extreme Components Analysis.

[BibT_eX]

[DOI]

Christopher K. I. Williams

Felix V. Agakov

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Wormholes Improve Contrastive Divergence.

[BibT_eX]

[DOI]

Andriy Mnih

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

On Improving the Efficiency of the Iterative Proportional Fitting Procedure.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002

Self Supervised Boosting.

[BibT_eX]

[DOI]

Richard S. Zemel

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning Sparse Topographic Representations with Products of Student-t Distributions.

[BibT_eX]

[DOI]

Simon Osindero

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A New Learning Algorithm for Mean Field Boltzmann Machines.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2002

2001

Positive tensor factorization.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2001

A Constrained EM Algorithm for Independent Component Analysis.

[BibT_eX]

[DOI]

Neural Comput., 2001

Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation.

[BibT_eX]

[DOI]

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

The Unified Propagation and Scaling Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000

Viewpoint-Invariant Learning and Detection of Human Heads.

[BibT_eX]

[DOI]

Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000), 2000

Unsupervised Learning of Models for Recognition.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2000, 6th European Conference on Computer Vision, Dublin, Ireland, June 26, 2000

Towards Automatic Discovery of Object Categories.

[BibT_eX]

[DOI]