Ignasi Clavera
Reinforcement Learning · 2017–2025
A researcher in the Science corpus: 9 papers; trusts 314 researchers and is trusted by 81 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 217 citations into it; #610 of 2,242 by trust here, #467 by citations
- Artificial Intelligence — 207 citations into it; #3,247 of 35,345 by trust here, #3,842 by citations
- Control and Systems Engineering — 89 citations into it
- Computer Vision and Pattern Recognition — 58 citations into it
- Optimization & Training — 36 citations into it
- Computational Theory and Mathematics — 29 citations into it
- Biomedical Engineering — 28 citations into it; #6,373 of 10,734 by trust here, #3,764 by citations
- Representation & Self-Supervised Learning — 26 citations into it
Whom Ignasi Clavera trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sergey Levine
- Pieter Abbeel
- John Schulman
- Richard S. Sutton
- Diederik P. Kingma
- Jan Peters
- Geoffrey E. Hinton
- Chelsea Finn
- E. Todorov
- Yoshua Bengio
Who trusts Ignasi Clavera overall
- Anusha Nagabandi
- Sergey Levine
- Youngmin Oh
- Chelsea Finn
- Tianhe Yu
- Pieter Abbeel
- Han-Jia Ye
- Brandon Amos
- Christian F. Perez
- Ron Dorfman
Papers from Ignasi Clavera's perspective
Ordered by how strongly the researchers Ignasi Clavera trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Model-Ensemble Trust-Region Policy Optimization (2018) — 487 citations
- Benchmarking Model-Based Reinforcement Learning (2019) — 394 citations
- Model-Based Reinforcement Learning via Meta-Policy Optimization (2018) — 259 citations
- Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning (2018) — 659 citations
- ProMP: Proximal Meta-Policy Search (2018) — 227 citations
- Policy transfer via modularity and reward guiding (2017) — 41 citations
- Model-Augmented Actor-Critic: Backpropagating through Paths (2020) — 96 citations
- OpenAI GPT-5 System Card (2025) — 667 citations
- Learning to Adapt: Meta-Learning for Model-Based Control (2018) — 94 citations