Lars Buesing
- Imagination-Augmented Agents for Deep Reinforcement Learning
2017/07/19 by Théophane Weber, Sébastien Racanière, Weber, Théophane +26 · 22 citations
Computer Science · #Reinforcement Learning in Robotics
- Representation Learning via Invariant Causal Mechanisms
2020/10/15 by Jovana Mitrovic, Brian McWilliams, Mitrovic, Jovana +7 · 18 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Multimodal Machine Learning Applications
- Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
2018/11/15 by Lars Buesing, Buesing, Lars, Théophane Weber +11 · 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 #Reinforcement Learning in Robotics
- Black box variational inference for state space models
2015/11/23 by Evan Archer, Archer, Evan, Il Memming Park +7 · 7 citations
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
2022/01/13 by Nenad Tomašev, Tomasev, Nenad, Ioana Bica +11 · 7 citations
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications
- Amplifying human performance in combinatorial competitive programming
2024/11/29 by Petar Veličković, Veličković, Petar, Alex Vitvitskyi +11 · 3 voices · 5 citations
Computer Science · Psychology · #AI-based Problem Solving and Planning #Educational Games and Gamification #Teaching and Learning Programming #cs.AI #cs.LG #cs.NE #cs.PL
- On the role of planning in model-based deep reinforcement learning
2020/11/08 by Jessica B. Hamrick, Hamrick, Jessica B., Abram L. Friesen +17 · 5 citations
Computer Science · #Artificial Intelligence (cs.AI) #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Robotic Path Planning Algorithms
- AI co-mathematician: Accelerating mathematicians with agentic AI
2026/05/07 by Daniel Zheng, Ingrid von Glehn, Yori Zwols +15 · 6 voices · 2 citations
#cs.AI
- Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
2020/04/23 by Giambattista Parascandolo, Lars Buesing, Parascandolo, Giambattista +15 · 1 citation
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
- Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
2017/11/06 by Artur Speiser, Jinyao Yan, Speiser, Artur +9 · 3 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · #Advanced Fluorescence Microscopy Techniques #Advanced Memory and Neural Computing #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC)
- Combining Q-Learning and Search with Amortized Value Estimates
2019/12/05 by Jessica B. Hamrick, Hamrick, Jessica B., Victor Bapst +11 · 1 citation
Computer Science · #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Metaheuristic Optimization Algorithms Research #Reinforcement Learning in Robotics