Ryan P. Adams
- Scalable Bayesian Optimization Using Deep Neural Networks
2015/02/19 by Jasper Snoek, Oren Rippel, Snoek, Jasper +15 · 2 voices · 58 citations
Computer Science · #Advanced Multi-Objective Optimization Algorithms #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification #stat.ML
- Taking the Human Out of the Loop: A Review of Bayesian Optimization
2015/12/10 by Bobak Shahriari, Kevin Swersky, Ziyu Wang +2 · 356 citations
Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #Gaussian Processes and Bayesian Inference
- Los carnavales de La Bañeza: Aspectos antropológicos
1976/01/01 by Rafael Gómez-Bombarelli, Jennifer N. Wei, David Duvenaud +8 · 2 voices · 82 citations
Arts and Humanities · Computer Science · Environmental Science · Materials Science · #Chemistry and Chemical Engineering #Computational Drug Discovery Methods #Cultural and Mythological Studies #Historical and Literary Analyses #Machine Learning in Materials Science #Spanish Literature and Culture Studies #cs.LG #physics.chem-ph
- Gradient-based Hyperparameter Optimization through Reversible Learning
2015/02/11 by Dougal Maclaurin, David Duvenaud, Maclaurin, Dougal +3 · 1 voice · 51 citations
Computer Science · #Machine Learning and Data Classification #Gaussian Processes and Bayesian Inference #Advanced Neural Network Applications
- Practical Bayesian Optimization of Machine Learning Algorithms
2012/06/13 by Jasper Snoek, Hugo Larochelle, Snoek, Jasper +3 · 389 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms #Machine Learning and Data Classification
- Spectral Representations for Convolutional Neural Networks
2015/06/11 by Oren Rippel, Jasper Snoek, Rippel, Oren +3 · 1 voice · 11 citations
Computer Science · Engineering · #Advanced Neural Network Applications #Machine Learning and ELM #Sparse and Compressive Sensing Techniques #cs.LG #stat.ML
- Probabilistic Backpropagation for Scalable Learning of Bayesian Neural\n Networks
2015/02/18 by José Miguel Hernández-Lobato, Ryan P. Adams, Hernández-Lobato, José Miguel +1 · 89 citations
Computer Science · #Machine Learning and Data Classification #Advanced Neural Network Applications #Bayesian Modeling and Causal Inference
- Convolutional Networks on Graphs for Learning Molecular Fingerprints
2015/09/30 by David Duvenaud, Duvenaud, David, Dougal Maclaurin +11 · 50 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Neural and Evolutionary Computing (cs.NE) #Protein Structure and Dynamics
- Bayesian Online Changepoint Detection
2007/10/19 by Ryan P. Adams, Adams, Ryan Prescott, David Mackay +1 · 24 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (stat.ML) #Statistical Methods and Inference
- Composing graphical models with neural networks for structured representations and fast inference
2016/03/20 by Matthew Johnson, David Duvenaud, Johnson, Matthew J. +7 · 34 citations
Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Neural Networks and Applications #Time Series Analysis and Forecasting
- Motivating the Rules of the Game for Adversarial Example Research
2018/07/18 by Justin Gilmer, Gilmer, Justin, Ryan P. Adams +8 · 1 voice · 15 citations
Computer Science · Mathematics · #Advanced Malware Detection Techniques #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Security and Verification in Computing #cs.LG #stat.ML
- Bayesian reaction optimization as a tool for chemical synthesis
2021/02/03 by Benjamin J. Shields, Jason M. Stevens, Jason Stevens +7 · 27 citations
Computer Science · Engineering · Materials Science · #Computational Drug Discovery Methods #Innovative Microfluidic and Catalytic Techniques Innovation #Machine Learning in Materials Science
- Input Warping for Bayesian Optimization of Non-stationary Functions
2014/02/05 by Jasper Snoek, Kevin Swersky, Snoek, Jasper +5 · 13 citations
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Freeze-Thaw Bayesian Optimization
2014/06/16 by Kevin Swersky, Jasper Snoek, Swersky, Kevin +3 · 13 citations
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Bayesian Optimization with Unknown Constraints
2014/03/22 by Michael A. Gelbart, Gelbart, Michael A., Jasper Snoek +3 · 11 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Learning Ordered Representations with Nested Dropout
2014/02/05 by Oren Rippel, Michael A. Gelbart, Rippel, Oren +3 · 14 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Domain Adaptation and Few-Shot Learning #Advanced Neural Network Applications
- Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
2021/07/13 by Dibya Ghosh, Jad Rahme, Ghosh, Dibya +9 · 14 citations
Computer Science · #Reinforcement Learning in Robotics #Machine Learning and Algorithms #Adversarial Robustness in Machine Learning
- Predictive Entropy Search for Bayesian Optimization with Unknown Constraints
2015/02/18 by José Miguel Hernández-Lobato, Michael A. Gelbart, Hernández-Lobato, José Miguel +7 · 9 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Machine Learning and Algorithms
- Slice sampling covariance hyperparameters of latent Gaussian models
2010/06/04 by Iain Murray, Ryan P. Adams, Murray, Iain +1 · 6 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
- Variational Boosting: Iteratively Refining Posterior Approximations
2016/11/20 by Andrew C. Miller, Nicholas Foti, Miller, Andrew C. +4 · 2 voices · 4 citations
Computer Science · Mathematics · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #cs.LG #stat.ME #stat.ML
- Discovering Latent Network Structure in Point Process Data
2014/02/04 by Scott W. Linderman, Ryan P. Adams, Linderman, Scott W. +1 · 4 citations
Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Point processes and geometric inequalities
- SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
2019/05/28 by Igor Fedorov, Fedorov, Igor, Ryan P. Adams +5 · 1 voice · 1 citation
Computer Science · #Advanced Neural Network Applications #Anomaly Detection Techniques and Applications #Video Surveillance and Tracking Methods #cs.CV #cs.LG
- Recurrent switching linear dynamical systems
2016/10/26 by Scott W. Linderman, Linderman, Scott W., Andrew C. Miller +9 · 4 citations
Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
- SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design
2020/07/16 by Ari Seff, Yaniv Ovadia, Seff, Ari +5 · 4 citations
Engineering · #3D Shape Modeling and Analysis #Design Education and Practice #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Manufacturing Process and Optimization
- A General Framework for Constrained Bayesian Optimization using Information-based Search
2015/11/30 by José Miguel Hernández-Lobato, Michael A. Gelbart, Hernández-Lobato, José Miguel +7 · 2 citations
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Learning the Parameters of Determinantal Point Process Kernels
2014/02/20 by Raja Hafiz Affandi, Affandi, Raja Hafiz, Emily B. Fox +5 · 2 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Point processes and geometric inequalities
- A framework for studying synaptic plasticity with neural spike train\n data
2014/11/14 by Scott W. Linderman, Christopher H. Stock, Linderman, Scott W. +3 · 2 citations
Neuroscience · Engineering · #Neural dynamics and brain function #Advanced Memory and Neural Computing #Neuroscience and Neuropharmacology Research
- Automated discovery of reprogrammable nonlinear dynamic metamaterials
2024/03/12 by Giovanni Bordiga, Bordiga, Giovanni, Eder Medina +11 · 3 citations
Engineering · #Advanced Materials and Mechanics #Applied Physics (physics.app-ph) #Dynamics and Control of Mechanical Systems #FOS: Physical sciences #Modular Robots and Swarm Intelligence
- PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
2017/09/26 by Jonathan H. Huggins, Huggins, Jonathan H., Ryan P. Adams +3 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Methods and Inference
- Tree-Structured Stick Breaking Processes for Hierarchical Data
2010/06/05 by Ryan P. Adams, Adams, Ryan Prescott, Zoubin Ghahramani +3 · 1 citation
Computer Science · #Advanced Clustering Algorithms Research #Bayesian Methods and Mixture Models #Data Management and Algorithms #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
- Generative Marginalization Models
2023/10/19 by Sulin Liu, Liu, Sulin, Peter J. Ramadge +3 · 1 voice · 1 citation
#cs.LG #cs.AI
- Meta-PDE: Learning to Solve PDEs Quickly Without a Mesh
2022/11/03 by Tian Qin, Alex Beatson, Qin, Tian +7 · 1 citation
Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks
- Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
2017/04/17 by Ardavan Saeedi, Saeedi, Ardavan, Matthew D. Hoffman +9 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Real-time design of architectural structures with differentiable mechanics and neural networks
2024/09/04 by Rafael Pastrana, Eder Medina, Pastrana, Rafael +7 · 1 citation
Engineering · Earth and Planetary Sciences · #Architecture and Computational Design #3D Surveying and Cultural Heritage #BIM and Construction Integration