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Ryan P. Adams

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

40

Venues

9

Active years

2013–2025

Best venue rank

A*

Where they publish

Papers

40 indexed papers, newest first.

YearVenueTitleAuthors
2025ICLRDesigning Mechanical Meta-Materials by Learning Equivariant Flows.Mehran Mirramezani, Anne S. Meeussen, Katia Bertoldi, Peter Orbanz, Ryan P. Adams
2025ICLRReal-time design of architectural structures with differentiable mechanics and neural networks.Rafael Pastrana, Eder Medina, Isabel M. de Oliveira, Sigrid Adriaenssens, Ryan P. Adams
2025ICLRGraph Neural Networks Gone Hogwild.Olga Solodova, Nick Richardson, Deniz Oktay, Ryan P. Adams
2025ICMLEfficiently Vectorized MCMC on Modern Accelerators.Hugh Dance, Pierre Glaser, Peter Orbanz, Ryan P. Adams
2025ICMLDiagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrdinger Equation.Kevin Han Huang, Ni Zhan, Elif Ertekin, Peter Orbanz, Ryan P. Adams
2024ICLRFiber Monte Carlo.Nick Richardson, Deniz Oktay, Yaniv Ovadia, James C. Bowden, Ryan P. Adams
2024ICMLGenerative Marginalization Models.Sulin Liu, Peter J. Ramadge, Ryan P. Adams
2023ICLRNeuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity.Deniz Oktay, Mehran Mirramezani, Eder Medina, Ryan P. Adams
2022ICLRVitruvion: A Generative Model of Parametric CAD Sketches.Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams
2021ICLRRandomized Automatic Differentiation.Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P. Adams
2021UAIActive multi-fidelity Bayesian online changepoint detection.Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
2020ICLRSUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models.Yucen Luo, Alex Beatson, Mohammad Norouzi, Jun Zhu, David Duvenaud, Ryan P. Adams, Ricky T. Q. Chen
2020ICMLAmortized Finite Element Analysis for Fast PDE-Constrained Optimization.Tianju Xue, Alex Beatson, Sigrid Adriaenssens, Ryan P. Adams
2019ICLRNon-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach.Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz
2019ICMLEfficient optimization of loops and limits with randomized telescoping sums.Alex Beatson, Ryan P. Adams
2018AISTATSMultimodal Prediction and Personalization of Photo Edits with Deep Generative Models.Ardavan Saeedi, Matthew D. Hoffman, Stephen J. DiVerdi, Asma Ghandeharioun, Matthew J. Johnson, Ryan P. Adams
2017AISTATSBayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems.Scott W. Linderman, Matthew J. Johnson, Andrew C. Miller, Ryan P. Adams, David M. Blei, Liam Paninski
2017ICMLVariational Boosting: Iteratively Refining Posterior Approximations.Andrew C. Miller, Nicholas J. Foti, Ryan P. Adams
2016AISTATSEarly Stopping as Nonparametric Variational Inference.David Duvenaud, Dougal Maclaurin, Ryan P. Adams
2016ICMLPredictive Entropy Search for Multi-objective Bayesian Optimization.Daniel Hernndez-Lobato, Jos Miguel Hernndez-Lobato, Amar Shah, Ryan P. Adams
2016ICMLThe Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM.Ardavan Saeedi, Matthew D. Hoffman, Matthew J. Johnson, Ryan P. Adams
2016ICRAVariability and predictability in tactile sensing during grasping.Qian Wan, Ryan P. Adams, Robert D. Howe
2015AAAIGraph-Sparse LDA: A Topic Model with Structured Sparsity.Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams
2015ICMLPredictive Entropy Search for Bayesian Optimization with Unknown Constraints.Jos Miguel Hernndez-Lobato, Michael A. Gelbart, Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani
2015ICMLProbabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks.Jos Miguel Hernndez-Lobato, Ryan P. Adams
2015ICMLGradient-based Hyperparameter Optimization through Reversible Learning.Dougal Maclaurin, David Duvenaud, Ryan P. Adams
2015ICMLCeleste: Variational inference for a generative model of astronomical images.Jeffrey Regier, Andrew C. Miller, Jon McAuliffe, Ryan P. Adams, Matthew D. Hoffman, Dustin Lang, David Schlegel, Prabhat
2015ICMLScalable Bayesian Optimization Using Deep Neural Networks.Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams
2014AISTATSAvoiding pathologies in very deep networks.David Duvenaud, Oren Rippel, Ryan P. Adams, Zoubin Ghahramani
2014ASPLOSASC: automatically scalable computation.Amos Waterland, Elaine Angelino, Ryan P. Adams, Jonathan Appavoo, Margo I. Seltzer
2014ICMLLearning the Parameters of Determinantal Point Process Kernels.Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Benjamin Taskar
2014ICMLDiscovering Latent Network Structure in Point Process Data.Scott W. Linderman, Ryan P. Adams
2014ICMLFactorized Point Process Intensities: A Spatial Analysis of Professional Basketball.Andrew C. Miller, Luke Bornn, Ryan P. Adams, Kirk Goldsberry
2014ICMLLearning Ordered Representations with Nested Dropout.Oren Rippel, Michael A. Gelbart, Ryan P. Adams
2014ICMLInput Warping for Bayesian Optimization of Non-Stationary Functions.Jasper Snoek, Kevin Swersky, Richard S. Zemel, Ryan P. Adams
2014UAIAccelerating MCMC via Parallel Predictive Prefetching.Elaine Angelino, Eddie Kohler, Amos Waterland, Margo I. Seltzer, Ryan P. Adams
2014UAIBayesian Optimization with Unknown Constraints.Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
2014UAIFirefly Monte Carlo: Exact MCMC with Subsets of Data.Dougal Maclaurin, Ryan P. Adams
2013IJCAIBootstrap Learning via Modular Concept Discovery.Eyal Dechter, Jonathan Malmaud, Ryan P. Adams, Joshua B. Tenenbaum
2013SYSTORComputational caches.Amos Waterland, Elaine Angelino, Ekin D. Cubuk, Efthimios Kaxiras, Ryan P. Adams, Jonathan Appavoo, Margo I. Seltzer