George Papamakarios
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
2025/07/07 by Gheorghe Comanici, Comanici, Gheorghe, Eric Bieber +6844 · 8 voices · 1390 citations
#cs.CL #cs.AI
- Normalizing Flows for Probabilistic Modeling and Inference
2019/12/05 by George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende +2 · 1 voice · 110 citations
#stat.ML #cs.LG
- A Generalist Neural Algorithmic Learner
2022/09/22 by Borja Ibarz, Ibarz, Borja, Vitaly Kurin +27 · 2 voices · 4 citations
Computer Science · #Machine Learning and Algorithms #Advanced Graph Neural Networks #Advanced Neural Network Applications
- Masked Autoregressive Flow for Density Estimation
2017/05/19 by George Papamakarios, Papamakarios, George, Theo Pavlakou +3 · 83 citations
Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- Neural Spline Flows
2019/06/10 by Conor Durkan, Artur Bekasov, Durkan, Conor +5 · 72 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Cell Image Analysis Techniques #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- Gemini: A Family of Highly Capable Multimodal Models
2023/12/19 by Gemini Robotics Team, Rohan Anil, Gemini Team +2692 · 9 voices · 6 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #cs.AI #cs.CL #cs.CV
- Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows
2018/05/18 by George Papamakarios, David C. Sterratt, Papamakarios, George +3 · 31 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) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks
- Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation
2016/05/20 by George Papamakarios, Iain Murray, Papamakarios, George +1 · 20 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference
- On Contrastive Learning for Likelihood-free Inference
2020/02/10 by Conor Durkan, Iain Murray, Durkan, Conor +3 · 11 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms
- Compositional Score Modeling for Simulation-based Inference
2022/09/28 by Tomas Geffner, George Papamakarios, Geffner, Tomas +3 · 7 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Machine Learning and Algorithms #Topic Modeling
- Neural Density Estimation and Likelihood-free Inference
2019/10/29 by George Papamakarios, Papamakarios, George · 4 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- Estimating Gibbs free energies via isobaric-isothermal flows
2023/05/22 by Peter Wirnsberger, Borja Ibarz, Wirnsberger, Peter +3 · 2 citations
Materials Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Statistical Mechanics (cond-mat.stat-mech) #Theoretical and Computational Physics