Richard E. Turner
- Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning
2018/05/22 by Aapo Hyvärinen, Hyvarinen, Aapo, Hiroaki Sasaki +3 · 31 citations
Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural Networks and Reservoir Computing
- Rényi Divergence Variational Inference
2016/02/06 by Yingzhen Li, Richard E. Turner, Li, Yingzhen +1 · 22 citations
Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
2016/11/07 by Shixiang Gu, Timothy Lillicrap, Gu, Shixiang +7 · 28 citations
Computer Science · Engineering · #Reinforcement Learning in Robotics #Fuel Cells and Related Materials #Advanced Neural Network Applications
- PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers
2023/08/10 by Phillip Lippe, Lippe, Phillip, Bastiaan S. Veeling +7 · 32 citations
Physics and Astronomy · Earth and Planetary Sciences · Engineering · #Model Reduction and Neural Networks #Meteorological Phenomena and Simulations #Lattice Boltzmann Simulation Studies
- A Foundation Model for the Earth System
2024/05/20 by Cristian Bodnar, Wessel P. Bruinsma, Bodnar, Cristian +36 · 3 voices · 16 citations
Physics and Astronomy · #Solar and Space Plasma Dynamics #cs.LG #physics.ao-ph
- Gradient Estimators for Implicit Models
2017/05/19 by Yingzhen Li, Li, Yingzhen, Richard E. Turner +1 · 11 citations
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks
- Conditional Density Estimation with Bayesian Normalising Flows
2018/02/14 by Brian L. Trippe, Richard E. Turner, Trippe, Brian L +1 · 8 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference
- Structured Evolution with Compact Architectures for Scalable Policy\n Optimization
2018/04/06 by Krzysztof Choromański, Mark Rowland, Choromanski, Krzysztof +7 · 7 citations
Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Robotics (cs.RO) #Stochastic Gradient Optimization Techniques
- Streaming Sparse Gaussian Process Approximations
2017/05/19 by Thang D. Bui, Cuong V. Nguyen, Bui, Thang D. +3 · 5 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML)
- Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge
2020/07/23 by Zichao Wang, Angus Lamb, Wang, Zichao +21 · 6 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Computers and Society (cs.CY) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Intelligent Tutoring Systems and Adaptive Learning #Machine Learning (cs.LG) #Machine Learning and Algorithms
- Continual Deep Learning by Functional Regularisation of Memorable Past
2020/04/29 by Pingbo Pan, Pan, Pingbo, Siddharth Swaroop +9 · 6 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Deep Gaussian Processes for Regression using Approximate Expectation Propagation
2016/02/12 by Thang D. Bui, Bui, Thang D., Daniel Hernández-Lobato +7 · 5 citations
Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Target Tracking and Data Fusion in Sensor Networks
- Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
2020/07/02 by Andrew Y. K. Foong, Foong, Andrew Y. K., Wessel P. Bruinsma +9 · 5 citations
Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
- Black-box α-divergence Minimization
2015/11/10 by José Miguel Hernández-Lobato, Hernández-Lobato, José Miguel, Yingzhen Li +10 · 4 citations
Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Neural Networks and Applications #Fault Detection and Control Systems
- Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
2023/11/01 by Runa Eschenhagen, Alexander Immer, Eschenhagen, Runa +7 · 8 citations
Computer Science · #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques #Machine Learning and Data Classification
- On conditional diffusion models for PDE simulations
2024/10/21 by Aliaksandra Shysheya, Cristiana Diaconu, Shysheya, Aliaksandra +11 · 12 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Machine Learning in Healthcare
- A Fourier Space Perspective on Diffusion Models
2025/05/16 by Fabian Falck, Falck, Fabian, Teodora Pandeva +14 · 1 voice · 13 citations
Computer Science · Biochemistry, Genetics and Molecular Biology · Medicine · #stat.ML #cs.CV #cs.LG #stat.ME
- Environmental Sensor Placement with Convolutional Gaussian Neural Processes
2022/11/18 by Tom R. Andersson, Andersson, Tom R., Wessel P. Bruinsma +18 · 5 citations
Computer Science · Environmental Science · #Gaussian Processes and Bayesian Inference #Air Quality Monitoring and Forecasting #Species Distribution and Climate Change
- Autoregressive Conditional Neural Processes
2023/03/25 by Wessel P. Bruinsma, Bruinsma, Wessel P., Stratis Markou +15 · 5 citations
Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Aardvark weather: end-to-end data-driven weather forecasting
2024/03/30 by Anna Vaughan, Vaughan, Anna, Stratis Markou +19 · 3 voices · 1 citation
Environmental Science · #Hydrological Forecasting Using AI #cs.LG #physics.ao-ph
- The Multivariate Generalised von Mises distribution: Inference and applications
2016/02/16 by Alexandre K. W. Navarro, Navarro, Alexandre K. W., Jes Frellsen +3 · 2 citations
Computer Science · #Bayesian Methods and Mixture Models #Gaussian Processes and Bayesian Inference #Bayesian Modeling and Causal Inference
- The Gaussian Neural Process
2021/01/10 by Wessel P. Bruinsma, James Requeima, Bruinsma, Wessel P. +7 · 3 citations
Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Influence Functions for Scalable Data Attribution in Diffusion Models
2024/10/17 by Bruno Mlodozeniec, Runa Eschenhagen, Mlodozeniec, Bruno +9 · 6 citations
Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #Opinion Dynamics and Social Influence
- Transformer Neural Autoregressive Flows
2024/01/03 by Massimiliano Patacchiola, Patacchiola, Massimiliano, Aliaksandra Shysheya +5 · 3 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Generative Adversarial Networks and Image Synthesis #Neural Networks and Applications
- Practical Conditional Neural Processes Via Tractable Dependent Predictions
2022/03/16 by Stratis Markou, Markou, Stratis, James Requeima +7 · 2 citations
Computer Science · #Anomaly Detection Techniques and Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
- Denoising Diffusion Probabilistic Models in Six Simple Steps
2024/02/06 by Richard E. Turner, Turner, Richard E., Cristiana-Diana Diaconu +9 · 1 voice · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
- Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
2024/02/05 by Lin Wu, Lin, Wu, Felix Dangel +9 · 3 citations
Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Iterative Methods for Nonlinear Equations #Machine Learning (cs.LG) #Numerical methods in inverse problems #Optimization and Control (math.OC)
- Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
2025/07/07 by Anish Dhir, Dhir, Anish, Cristiana Diaconu +9 · 4 citations
Computer Science · Neuroscience · #Bayesian Modeling and Causal Inference #Gaussian Processes and Bayesian Inference #Functional Brain Connectivity Studies
- Convolutional conditional neural processes for local climate downscaling
2021/01/20 by Anna Vaughan, Vaughan, Anna, Will Tebbutt +5 · 1 citation
Environmental Science · Earth and Planetary Sciences · #Climate variability and models #Cryospheric studies and observations #Climate change and permafrost
- Geometric Neural Diffusion Processes
2023/07/11 by Emile Mathieu, Mathieu, Emile, Vincent Dutordoir +9 · 1 voice · 1 citation
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
- Fresh in memory: Training-order recency is linearly encoded in language model activations
2025/09/17 by Dmitrii Krasheninnikov, Richard E. Turner, Krasheninnikov, Dmitrii +3 · 3 voices · 1 citation
Computer Science · #Natural Language Processing Techniques #Topic Modeling #cs.AI #cs.CL #cs.LG
- Diffusion-Augmented Neural Processes
2023/11/16 by Lorenzo Bonito, Bonito, Lorenzo, James Requeima +5 · 1 citation
Computer Science · #FOS: Computer and information sciences #I.2.6 #Machine Learning (cs.LG) #Machine Learning in Healthcare
- Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC
2023/12/09 by Lin Wu, Lin, Wu, Felix Dangel +11 · 1 citation
Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #FOS: Computer and information sciences #Geophysical and Geoelectrical Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Model Reduction and Neural Networks
- Translation Equivariant Transformer Neural Processes
2024/06/18 by Matthew Ashman, Cristiana Diaconu, Ashman, Matthew +13 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- In-Context In-Context Learning with Transformer Neural Processes
2024/06/19 by Matthew Ashman, Ashman, Matthew, Cristiana Diaconu +5 · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications