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"Latent Space Optimization with Deep Generative Models"
Jose Miguel Hernandez-Lobato
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Jose Miguel Hernandez-Lobato (University of Cambridge)
More from the Same Authors
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2023 : Leveraging Task Structures for Improved Identifiability in Neural Network Representations »
Wenlin Chen · Julien Horwood · Juyeon Heo · Jose Miguel Hernandez-Lobato -
2023 : Minimal Random Code Learning with Mean-KL Parameterization »
Jihao Andreas Lin · Gergely Flamich · Jose Miguel Hernandez-Lobato -
2022 Poster: Adapting the Linearised Laplace Model Evidence for Modern Deep Learning »
Javier Antorán · David Janz · James Allingham · Erik Daxberger · Riccardo Barbano · Eric Nalisnick · Jose Miguel Hernandez-Lobato -
2022 Spotlight: Adapting the Linearised Laplace Model Evidence for Modern Deep Learning »
Javier Antorán · David Janz · James Allingham · Erik Daxberger · Riccardo Barbano · Eric Nalisnick · Jose Miguel Hernandez-Lobato -
2022 Poster: Action-Sufficient State Representation Learning for Control with Structural Constraints »
Biwei Huang · Chaochao Lu · Liu Leqi · Jose Miguel Hernandez-Lobato · Clark Glymour · Bernhard Schölkopf · Kun Zhang -
2022 Spotlight: Action-Sufficient State Representation Learning for Control with Structural Constraints »
Biwei Huang · Chaochao Lu · Liu Leqi · Jose Miguel Hernandez-Lobato · Clark Glymour · Bernhard Schölkopf · Kun Zhang -
2022 Poster: Fast Relative Entropy Coding with A* coding »
Gergely Flamich · Stratis Markou · Jose Miguel Hernandez-Lobato -
2022 Spotlight: Fast Relative Entropy Coding with A* coding »
Gergely Flamich · Stratis Markou · Jose Miguel Hernandez-Lobato -
2021 Poster: Active Slices for Sliced Stein Discrepancy »
Wenbo Gong · Kaibo Zhang · Yingzhen Li · Jose Miguel Hernandez-Lobato -
2021 Spotlight: Active Slices for Sliced Stein Discrepancy »
Wenbo Gong · Kaibo Zhang · Yingzhen Li · Jose Miguel Hernandez-Lobato -
2021 Poster: A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization »
Andrew Campbell · Wenlong Chen · Vincent Stimper · Jose Miguel Hernandez-Lobato · Yichuan Zhang -
2021 Spotlight: A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization »
Andrew Campbell · Wenlong Chen · Vincent Stimper · Jose Miguel Hernandez-Lobato · Yichuan Zhang -
2021 Poster: Bayesian Deep Learning via Subnetwork Inference »
Erik Daxberger · Eric Nalisnick · James Allingham · Javier Antorán · Jose Miguel Hernandez-Lobato -
2021 Spotlight: Bayesian Deep Learning via Subnetwork Inference »
Erik Daxberger · Eric Nalisnick · James Allingham · Javier Antorán · Jose Miguel Hernandez-Lobato -
2020 : Invited Talk: Efficient Missing-value Acquisition with Variational Autoencoders »
Jose Miguel Hernandez-Lobato -
2020 Poster: Reinforcement Learning for Molecular Design Guided by Quantum Mechanics »
Gregor Simm · Robert Pinsler · Jose Miguel Hernandez-Lobato -
2020 Poster: A Generative Model for Molecular Distance Geometry »
Gregor Simm · Jose Miguel Hernandez-Lobato -
2019 Poster: Dropout as a Structured Shrinkage Prior »
Eric Nalisnick · Jose Miguel Hernandez-Lobato · Padhraic Smyth -
2019 Oral: Dropout as a Structured Shrinkage Prior »
Eric Nalisnick · Jose Miguel Hernandez-Lobato · Padhraic Smyth -
2019 Poster: EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE »
Chao Ma · Sebastian Tschiatschek · Konstantina Palla · Jose Miguel Hernandez-Lobato · Sebastian Nowozin · Cheng Zhang -
2019 Poster: Variational Implicit Processes »
Chao Ma · Yingzhen Li · Jose Miguel Hernandez-Lobato -
2019 Oral: Variational Implicit Processes »
Chao Ma · Yingzhen Li · Jose Miguel Hernandez-Lobato -
2019 Oral: EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE »
Chao Ma · Sebastian Tschiatschek · Konstantina Palla · Jose Miguel Hernandez-Lobato · Sebastian Nowozin · Cheng Zhang -
2018 Poster: Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning »
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft -
2018 Oral: Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning »
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft -
2017 Poster: Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space »
Jose Miguel Hernandez-Lobato · James Requeima · Edward Pyzer-Knapp · Alan Aspuru-Guzik -
2017 Poster: Grammar Variational Autoencoder »
Matt J. Kusner · Brooks Paige · Jose Miguel Hernandez-Lobato -
2017 Talk: Grammar Variational Autoencoder »
Matt J. Kusner · Brooks Paige · Jose Miguel Hernandez-Lobato -
2017 Talk: Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space »
Jose Miguel Hernandez-Lobato · James Requeima · Edward Pyzer-Knapp · Alan Aspuru-Guzik -
2017 Poster: Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control »
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Miguel Hernandez-Lobato · Richard E Turner · Douglas Eck -
2017 Talk: Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control »
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Miguel Hernandez-Lobato · Richard E Turner · Douglas Eck