← Authors

Ryan P. Adams

38 papers · 2008–2022 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (6) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (14) πŸ—ΊοΈ Taxonomy Completionist (21) 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (30) πŸ“› The Namer πŸ”¬ Deep Specialist (17) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ”₯ Unstoppable (11) πŸš€ Conference Pioneer πŸ’Ž Century Club (38) ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (86) πŸ“ˆ Trend Setter

Conferences

NIPS (30) JMLR (3) ICLR (2) AISTATS (1) ICML (1) UAI (1)

Top co-authors

Jasper Snoek (5) Diana Cai (4) Scott Linderman (3) Zoubin Ghahramani (3) Iain Murray (3) Kevin Swersky (3) Hugo Larochelle (2) Jordan Ash (2) Richard S. Zemel (2) David K. Duvenaud (2)

Keywords

bayesian inference (11) markov chain monte carlo (8) gaussian process (8) neural network (5) variational inference (4) latent variable model (4) bayesian optimization (4) probabilistic modeling (3) bayesian nonparametrics (3) slice sampling (3) convolutional neural network (3) generative model (3) generalized linear model (3) mixture model (3) message passing (2) hierarchical model (2) nonparametric bayesian (2) constrained optimization (2) topic modeling (2) feature extraction (2)

Papers

Multi-fidelity Monte Carlo: a pseudo-marginal approach NIPS 2022
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability NIPS 2021
Slice Sampling Reparameterization Gradients NIPS 2021
Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate NIPS 2021
Active multi-fidelity Bayesian online changepoint detection UAI 2021
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters NIPS 2020
Learning Composable Energy Surrogates for PDE Order Reduction NIPS 2020
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models ICLR 2020
On Warm-Starting Neural Network Training NIPS 2020
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers NIPS 2019
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach ICLR 2019
Discrete Object Generation with Reversible Inductive Construction NIPS 2019
A Bayesian Nonparametric View on Count-Min Sketch NIPS 2018
Reducing Reparameterization Gradient Variance NIPS 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NIPS 2017
Variational Boosting: Iteratively Refining Posterior Approximations ICML 2017
Bayesian latent structure discovery from multi-neuron recordings NIPS 2016
Composing graphical models with neural networks for structured representations and fast inference NIPS 2016
A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016
Convolutional Networks on Graphs for Learning Molecular Fingerprints NIPS 2015
Spectral Representations for Convolutional Neural Networks NIPS 2015
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NIPS 2015
A Gaussian Process Model of Quasar Spectral Energy Distributions NIPS 2015
A framework for studying synaptic plasticity with neural spike train data NIPS 2014
Parallel MCMC with Generalized Elliptical Slice Sampling JMLR 2014
A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NIPS 2013
Contrastive Learning Using Spectral Methods NIPS 2013
Multi-Task Bayesian Optimization NIPS 2013
Message Passing Inference with Chemical Reaction Networks NIPS 2013
Probabilistic n-Choose-k Models for Classification and Ranking NIPS 2012
Practical Bayesian Optimization of Machine Learning Algorithms NIPS 2012
Nonparametric Guidance of Autoencoder Representations using Label Information JMLR 2012
Cardinality Restricted Boltzmann Machines NIPS 2012
Priors for Diversity in Generative Latent Variable Models NIPS 2012
Learning the Structure of Deep Sparse Graphical Models AISTATS 2010
Tree-Structured Stick Breaking for Hierarchical Data NIPS 2010
Slice sampling covariance hyperparameters of latent Gaussian models NIPS 2010
The Gaussian Process Density Sampler NIPS 2008