Pablo Samuel Castro

According to our database1, Pablo Samuel Castro authored at least 61 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
A density estimation perspective on learning from pairwise human preferences.
Trans. Mach. Learn. Res., 2024

CALE: Continuous Arcade Learning Environment.
CoRR, 2024

Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL.
CoRR, 2024

NAVIX: Scaling MiniGrid Environments with JAX.
CoRR, 2024

In deep reinforcement learning, a pruned network is a good network.
CoRR, 2024

Mixture of Experts in a Mixture of RL settings.
RLJ, 2024

On the consistency of hyper-parameter selection in value-based deep reinforcement learning.
RLJ, 2024

Adaptive Accompaniment with ReaLchords.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mixtures of Experts Unlock Parameter Scaling for Deep RL.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

In value-based deep reinforcement learning, a pruned network is a good network.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes.
Trans. Mach. Learn. Res., 2023

Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy.
CoRR, 2023

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks.
CoRR, 2023

JaxPruner: A concise library for sparsity research.
CoRR, 2023

Offline Reinforcement Learning with On-Policy Q-Function Regularization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Small batch deep reinforcement learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Dormant Neuron Phenomenon in Deep Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Bigger, Better, Faster: Human-level Atari with human-level efficiency.
Proceedings of the International Conference on Machine Learning, 2023

The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Beyond Tabula Rasa: Reincarnating Reinforcement Learning.
CoRR, 2022

Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The State of Sparse Training in Deep Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

A general class of surrogate functions for stable and efficient reinforcement learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Losses, Dissonances, and Distortions.
CoRR, 2021

A functional mirror ascent view of policy gradient methods with function approximation.
CoRR, 2021

MICo: Learning improved representations via sampling-based state similarity for Markov decision processes.
CoRR, 2021

The Difficulty of Passive Learning in Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

MICo: Improved representations via sampling-based state similarity for Markov decision processes.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Reinforcement Learning at the Edge of the Statistical Precipice.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research.
Proceedings of the 38th International Conference on Machine Learning, 2021

Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Metrics and Continuity in Reinforcement Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Autonomous navigation of stratospheric balloons using reinforcement learning.
Nat., 2020

GANterpretations.
CoRR, 2020

Rigging the Lottery: Making All Tickets Winners.
Proceedings of the 37th International Conference on Machine Learning, 2020

Shaping the Narrative Arc: Information-Theoretic Collaborative DialoguePaper type: Technical Paper.
Proceedings of the Eleventh International Conference on Computational Creativity, 2020

Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Inverse Reinforcement Learning with Multiple Ranked Experts.
CoRR, 2019

Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue.
CoRR, 2019

A Geometric Perspective on Optimal Representations for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Performing Structured Improvisations with Pre-trained Deep Learning Models.
Proceedings of the Tenth International Conference on Computational Creativity, 2019

Distributional reinforcement learning with linear function approximation.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

A Comparative Analysis of Expected and Distributional Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
CoRR, 2018

Dopamine: A Research Framework for Deep Reinforcement Learning.
CoRR, 2018

Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation.
CoRR, 2018

2013
iBOAT: Isolation-Based Online Anomalous Trajectory Detection.
IEEE Trans. Intell. Transp. Syst., 2013

Real Time Anomalous Trajectory Detection and Analysis.
Mob. Networks Appl., 2013

From taxi GPS traces to social and community dynamics: A survey.
ACM Comput. Surv., 2013

2012
Urban Traffic Modelling and Prediction Using Large Scale Taxi GPS Traces.
Proceedings of the Pervasive Computing - 10th International Conference, 2012

2011
Real-Time Detection of Anomalous Taxi Trajectories from GPS Traces.
Proceedings of the Mobile and Ubiquitous Systems: Computing, Networking, and Services, 2011

Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metrics.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

2010
Smarter Sampling in Model-Based Bayesian Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Using Bisimulation for Policy Transfer in MDPs.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Equivalence Relations in Fully and Partially Observable Markov Decision Processes.
Proceedings of the IJCAI 2009, 2009

2007
Using Linear Programming for Bayesian Exploration in Markov Decision Processes.
Proceedings of the IJCAI 2007, 2007

2006
Methods for Computing State Similarity in Markov Decision Processes.
Proceedings of the UAI '06, 2006


  Loading...