Jos Miguel Hernndez-Lobato
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
71
Venues
13
Active years
2006–2025
Best venue rank
A*
Where they publish
Papers
71 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Training Neural Samplers with Reverse Diffusive KL Divergence. | Jiajun He, Wenlin Chen, Mingtian Zhang, David Barber, Jos Miguel Hernndez-Lobato |
| 2025 | ICLR | Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. | Richard Bergna, Sergio Calvo-Ordoez, Felix L. Opolka, Pietro Lio, Jos Miguel Hernndez-Lobato |
| 2025 | ICML | Aligning Multimodal Representations through an Information Bottleneck. | Antonio Almudvar, Jos Miguel Hernndez-Lobato, Sameer Khurana, Ricard Marxer, Alfonso Ortega |
| 2025 | ICML | Scalable Gaussian Processes with Latent Kronecker Structure. | Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat, David Eriksson, Jos Miguel Hernndez-Lobato, Eytan Bakshy |
| 2025 | ICML | Progressive Tempering Sampler with Diffusion. | Severi Rissanen, Ruikang Ouyang, Jiajun He, Wenlin Chen, Markus Heinonen, Arno Solin, Jos Miguel Hernndez-Lobato |
| 2025 | ICML | Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space. | Zixing Song, Ziqiao Meng, Jos Miguel Hernndez-Lobato |
| 2025 | KDD | Track and Tweak: Monitoring and Improving Group Fairness for Temporal Graph Neural Networks in Real Time. | Zixing Song, Muzhi Li, Yifei Zhang, Irwin King, Jos Miguel Hernndez-Lobato |
| 2025 | WWW | FedEDM: Federated Equivariant Diffusion Model for 3D Molecule Generation with Enhanced Communication Efficiency. | Zixing Song, Irwin King, Jos Miguel Hernndez-Lobato |
| 2024 | ICLR | RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations. | Jiajun He, Gergely Flamich, Zongyu Guo, Jos Miguel Hernndez-Lobato |
| 2024 | ICLR | Stochastic Gradient Descent for Gaussian Processes Done Right. | Jihao Andreas Lin, Shreyas Padhy, Javier Antorn, Austin Tripp, Alexander Terenin, Csaba Szepesvri, Jos Miguel Hernndez-Lobato, David Janz |
| 2024 | ICLR | Retro-fallback: retrosynthetic planning in an uncertain world. | Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, Jos Miguel Hernndez-Lobato |
| 2024 | ICML | Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation. | Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, Jos Miguel Hernndez-Lobato |
| 2024 | ICML | Diffusive Gibbs Sampling. | Wenlin Chen, Mingtian Zhang, Brooks Paige, Jos Miguel Hernndez-Lobato, David Barber |
| 2024 | ICML | Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens. | Ross M. Clarke, Jos Miguel Hernndez-Lobato |
| 2024 | ICML | Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. | Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jos Miguel Hernndez-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rgamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang |
| 2023 | ICLR | Sampling-based inference for large linear models, with application to linearised Laplace. | Javier Antorn, Shreyas Padhy, Riccardo Barbano, Eric T. Nalisnick, David Janz, Jos Miguel Hernndez-Lobato |
| 2023 | ICLR | Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction. | Wenlin Chen, Austin Tripp, Jos Miguel Hernndez-Lobato |
| 2023 | ICLR | Flow Annealed Importance Sampling Bootstrap. | Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schlkopf, Jos Miguel Hernndez-Lobato |
| 2022 | AISTATS | Resampling Base Distributions of Normalizing Flows. | Vincent Stimper, Bernhard Schlkopf, Jos Miguel Hernndez-Lobato |
| 2022 | ICLR | Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation. | Ross M. Clarke, Elre Talea Oldewage, Jos Miguel Hernndez-Lobato |
| 2022 | ICLR | Invariant Causal Representation Learning for Out-of-Distribution Generalization. | Chaochao Lu, Yuhuai Wu, Jos Miguel Hernndez-Lobato, Bernhard Schlkopf |
| 2022 | ICML | Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. | Javier Antorn, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, Jos Miguel Hernndez-Lobato |
| 2022 | ICML | Fast Relative Entropy Coding with A* coding. | Gergely Flamich, Stratis Markou, Jos Miguel Hernndez-Lobato |
| 2022 | ICML | Action-Sufficient State Representation Learning for Control with Structural Constraints. | Biwei Huang, Chaochao Lu, Liu Leqi, Jos Miguel Hernndez-Lobato, Clark Glymour, Bernhard Schlkopf, Kun Zhang |
| 2022 | WWW | BSODA: A Bipartite Scalable Framework for Online Disease Diagnosis. | Weijie He, Xiaohao Mao, Chao Ma, Yu Huang, Jos Miguel Hernndez-Lobato, Ting Chen |
| 2021 | AAAI | Educational Question Mining At Scale: Prediction, Analysis and Personalization. | Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, Jos Miguel Hernndez-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang |
| 2021 | AISTATS | Predictive Complexity Priors. | Eric T. Nalisnick, Jonathan Gordon, Jos Miguel Hernndez-Lobato |
| 2021 | ICLR | Sliced Kernelized Stein Discrepancy. | Wenbo Gong, Yingzhen Li, Jos Miguel Hernndez-Lobato |
| 2021 | ICLR | Getting a CLUE: A Method for Explaining Uncertainty Estimates. | Javier Antorn, Umang Bhatt, Tameem Adel, Adrian Weller, Jos Miguel Hernndez-Lobato |
| 2021 | ICLR | Activation-level uncertainty in deep neural networks. | Pablo Morales-Alvarez, Daniel Hernndez-Lobato, Rafael Molina, Jos Miguel Hernndez-Lobato |
| 2021 | ICLR | Symmetry-Aware Actor-Critic for 3D Molecular Design. | Gregor N. C. Simm, Robert Pinsler, Gbor Csnyi, Jos Miguel Hernndez-Lobato |
| 2021 | ICML | Active Slices for Sliced Stein Discrepancy. | Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jos Miguel Hernndez-Lobato |
| 2021 | ICML | A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization. | Andrew Campbell, Wenlong Chen, Vincent Stimper, Jos Miguel Hernndez-Lobato, Yichuan Zhang |
| 2021 | ICML | Bayesian Deep Learning via Subnetwork Inference. | Erik A. Daxberger, Eric T. Nalisnick, James Urquhart Allingham, Javier Antorn, Jos Miguel Hernndez-Lobato |
| 2020 | ICML | A Generative Model for Molecular Distance Geometry. | Gregor N. C. Simm, Jos Miguel Hernndez-Lobato |
| 2020 | ICML | Reinforcement Learning for Molecular Design Guided by Quantum Mechanics. | Gregor N. C. Simm, Robert Pinsler, Jos Miguel Hernndez-Lobato |
| 2020 | ISLPED | A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs. | Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, Jos Miguel Hernndez-Lobato, Gu-Yeon Wei |
| 2019 | ICLR | A Generative Model For Electron Paths. | John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, Jos Miguel Hernndez-Lobato |
| 2019 | ICLR | Generating Molecules via Chemical Reactions. | John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, Jos Miguel Hernndez-Lobato |
| 2019 | ICLR | Meta-Learning For Stochastic Gradient MCMC. | Wenbo Gong, Yingzhen Li, Jos Miguel Hernndez-Lobato |
| 2019 | ICLR | Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. | Marton Havasi, Robert Peharz, Jos Miguel Hernndez-Lobato |
| 2019 | ICLR | Deterministic Variational Inference for Robust Bayesian Neural Networks. | Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, Jos Miguel Hernndez-Lobato, Alexander L. Gaunt |
| 2019 | ICML | Variational Implicit Processes. | Chao Ma, Yingzhen Li, Jos Miguel Hernndez-Lobato |
| 2019 | ICML | EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. | Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jos Miguel Hernndez-Lobato, Sebastian Nowozin, Cheng Zhang |
| 2019 | ICML | Dropout as a Structured Shrinkage Prior. | Eric T. Nalisnick, Jos Miguel Hernndez-Lobato, Padhraic Smyth |
| 2018 | ESANN | Sensitivity analysis for predictive uncertainty. | Stefan Depeweg, Jos Miguel Hernndez-Lobato, Steffen Udluft, Thomas A. Runkler |
| 2018 | ICLR | Learning a Generative Model for Validity in Complex Discrete Structures. | David Janz, Jos van der Westhuizen, Brooks Paige, Matt J. Kusner, Jos Miguel Hernndez-Lobato |
| 2018 | ICML | Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning. | Stefan Depeweg, Jos Miguel Hernndez-Lobato, Finale Doshi-Velez, Steffen Udluft |
| 2017 | ICLR | Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks. | Stefan Depeweg, Jos Miguel Hernndez-Lobato, Finale Doshi-Velez, Steffen Udluft |
| 2017 | ICML | Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space. | Jos Miguel Hernndez-Lobato, James Requeima, Edward O. Pyzer-Knapp, Aln Aspuru-Guzik |
| 2017 | ICML | Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control. | Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, Jos Miguel Hernndez-Lobato, Richard E. Turner, Douglas Eck |
| 2017 | ICML | Grammar Variational Autoencoder. | Matt J. Kusner, Brooks Paige, Jos Miguel Hernndez-Lobato |
| 2017 | ISLPED | A case for efficient accelerator design space exploration via Bayesian optimization. | Brandon Reagen, Jos Miguel Hernndez-Lobato, Robert Adolf, Michael A. Gelbart, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks |
| 2016 | AISTATS | Scalable Gaussian Process Classification via Expectation Propagation. | Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato |
| 2016 | CVPR | Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. | Viktoriia Sharmanska, Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Novi Quadrianto |
| 2016 | ICML | Deep Gaussian Processes for Regression using Approximate Expectation Propagation. | Thang D. Bui, Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Yingzhen Li, Richard E. Turner |
| 2016 | ICML | Predictive Entropy Search for Multi-objective Bayesian Optimization. | Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Amar Shah, Ryan P. Adams |
| 2016 | ICML | Black-Box Alpha Divergence Minimization. | Jos Miguel Hernndez-Lobato, Yingzhen Li, Mark Rowland, Thang D. Bui, Daniel Hernndez-Lobato, Richard E. Turner |
| 2016 | ISCA | Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators. | Brandon Reagen, Paul N. Whatmough, Robert Adolf, Saketh Rama, Hyunkwang Lee, Sae Kyu Lee, Jos Miguel Hernndez-Lobato, Gu-Yeon Wei, David M. Brooks |
| 2015 | ICML | A Probabilistic Model for Dirty Multi-task Feature Selection. | Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Zoubin Ghahramani |
| 2015 | ICML | Predictive Entropy Search for Bayesian Optimization with Unknown Constraints. | Jos Miguel Hernndez-Lobato, Michael A. Gelbart, Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani |
| 2015 | ICML | Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks. | Jos Miguel Hernndez-Lobato, Ryan P. Adams |
| 2014 | ICML | Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. | Jos Miguel Hernndez-Lobato, Neil Houlsby, Zoubin Ghahramani |
| 2014 | ICML | Probabilistic Matrix Factorization with Non-random Missing Data. | Jos Miguel Hernndez-Lobato, Neil Houlsby, Zoubin Ghahramani |
| 2014 | ICML | Cold-start Active Learning with Robust Ordinal Matrix Factorization. | Neil Houlsby, Jos Miguel Hernndez-Lobato, Zoubin Ghahramani |
| 2013 | ICML | Gaussian Process Vine Copulas for Multivariate Dependence. | David Lopez-Paz, Jos Miguel Hernndez-Lobato, Zoubin Ghahramani |
| 2013 | ICML | Dynamic Covariance Models for Multivariate Financial Time Series. | Yue Wu, Jos Miguel Hernndez-Lobato, Zoubin Ghahramani |
| 2011 | IJCAI | Gaussianity Measures for Detecting the Direction of Causal Time Series. | Jos Miguel Hernndez-Lobato, Pablo Morales-Mombiela, Alberto Surez |
| 2007 | ICANN | GARCH Processes with Non-parametric Innovations for Market Risk Estimation. | Jos Miguel Hernndez-Lobato, Daniel Hernndez-Lobato, Alberto Surez |
| 2006 | ICANN | Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis. | Jos Miguel Hernndez-Lobato, Alberto Surez |
| 2006 | IDEAL | Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm. | Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Rubn Ruiz-Torrubiano, ngel Valle |