Phielipp, Mariano

24 publications

ICLRW 2025 CrystalGym: A New Benchmark for Materials Discovery Using Reinforcement Learning Prashant Govindarajan, Mathieu Reymond, Antoine Clavaud, Mariano Phielipp, Santiago Miret, Sarath Chandar

CoRL 2024 Accelerating Visual Sparse-Reward Learning with Latent Nearest-Demonstration-Guided Explorations Ruihan Zhao, Ufuk Topcu, Sandeep P. Chinchali, Mariano Phielipp

NeurIPSW 2024 Crystal Design Amidst Noisy DFT Signals: A Reinforcement Learning Approach Prashant Govindarajan, Mathieu Reymond, Santiago Miret, Mariano Phielipp, Sarath Chandar

NeurIPSW 2024 Efficient Design-and-Control Automation with Reinforcement Learning and Adaptive Exploration Jiajun Fan, Hongyao Tang, Michael Przystupa, Mariano Phielipp, Santiago Miret, Glen Berseth

ICLR 2024 Searching for High-Value Molecules Using Reinforcement Learning and Transformers Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth

ICLRW 2023 Behavioral Cloning for Crystal Design Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

NeurIPSW 2023 Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar

CoRL 2023 MOTO: Offline Pre-Training to Online Fine-Tuning for Model-Based Robot Learning Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D. Martin, Mariano Phielipp, Chelsea Finn

ICLRW 2023 MOTO: Offline to Online Fine-Tuning for Model-Based Reinforcement Learning Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D Martin, Mariano Phielipp, Chelsea Finn

ICLRW 2023 Model-Based Adversarial Imitation Learning as Online Fine-Tuning Rafael Rafailov, Victor Kolev, Kyle Beltran Hatch, John D Martin, Mariano Phielipp, Jiajun Wu, Chelsea Finn

NeurIPSW 2023 Searching for High-Value Molecules Using Reinforcement Learning and Transformers Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth

ICML 2022 AnyMorph: Learning Transferable Polices by Inferring Agent Morphology Brandon Trabucco, Mariano Phielipp, Glen Berseth

NeurIPSW 2022 Conformer Search Using SE3-Transformers and Imitation Learning Luca Thiede, Santiago Miret, Krzysztof Sadowski, Haoping Xu, Mariano Phielipp, Alan Aspuru-Guzik

ICML 2022 DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning Hassam Sheikh, Kizza Frisbee, Mariano Phielipp

NeurIPSW 2022 Group SELFIES: A Robust Fragment-Based Molecular String Representation Austin Henry Cheng, Andy Cai, Santiago Miret, Gustavo Malkomes, Mariano Phielipp, Alan Aspuru-Guzik

ICLRW 2022 Learning Transferable Policies by Inferring Agent Morphology Brandon Trabucco, Mariano Phielipp, Glen Berseth

ICLR 2022 Maximizing Ensemble Diversity in Deep Reinforcement Learning Hassam Sheikh, Mariano Phielipp, Ladislau Boloni

CoRL 2022 Modularity Through Attention: Efficient Training and Transfer of Language-Conditioned Policies for Robot Manipulation Yifan Zhou, Shubham Sonawani, Mariano Phielipp, Simon Stepputtis, Heni Amor

NeurIPSW 2022 Offline Policy Comparison with Confidence: Benchmarks and Baselines Anurag Koul, Mariano Phielipp, Alan Fern

NeurIPSW 2021 The Reflective Explorer: Online Meta-Exploration from Offline Data in Realistic Robotic Tasks Rafael Rafailov, Varun Kumar Vijay, Tianhe Yu, Avi Singh, Mariano Phielipp, Chelsea Finn

NeurIPS 2020 Instance-Based Generalization in Reinforcement Learning Martin Bertran, Natalia Martinez, Mariano Phielipp, Guillermo Sapiro

NeurIPS 2020 Language-Conditioned Imitation Learning for Robot Manipulation Tasks Simon Stepputtis, Joseph P. Campbell, Mariano Phielipp, Stefan Lee, Chitta Baral, Heni Ben Amor

NeurIPS 2019 Goal-Conditioned Imitation Learning Yiming Ding, Carlos Florensa, Pieter Abbeel, Mariano Phielipp

ICMLW 2019 Goal-Conditioned Imitation Learning Yiming Ding, Carlos Florensa, Mariano Phielipp, Pieter Abbeel