Shrouds: Optimal Separating Surfaces for Enumerated Volumes. - Gregory M. Nielson; Gary Graf; Ryan Holmes; Adam Huang; Mariano Phielipp (VisSym, 2003)

Can the high-level content of natural images be indexed using local analysis? - John A. Black Jr.; Mariano Phielipp; Gregory M. Nielson; Sethuraman Panchanathan (Human Vision and Electronic Imaging, 2004)

Description of a Modeling, Simulation, Animation, and Real-Time Control (MoSART) Environment for a Broad Class of Dynamical Systems. - Armando A. Rodriguez; Oguzhan Çifdalöz; Mariano Phielipp; Jeffrey J. Dickeson; Paul M. Koziol; David Miles; Miguel Garcia; Robert McCullen; Jerald Willis; Jose Benavides (CDC, 2006)

Using words as lexical basis functions for automatically indexing face images in a manner that correlates with human perception of similarity. - Mariano Phielipp; John A. Black Jr.; Sethuraman Panchanathan (Human Vision and Electronic Imaging, 2006)

Description of a Modeling, Simulation, Animation, and Real-Time Control (MoSART) Environment for a Class of 6-DOF Dynamical Systems. - Armando A. Rodriguez; Oguzhan Çifdalöz; Mariano Phielipp; Jeffrey J. Dickeson (ACC, 2007)

Fast, Accurate, and Practical Identity Inference Using TV Remote Controls. - Mariano Phielipp; Magdiel Galan; Richard Lee; Branislav Kveton; Jeffrey Hightower (IAAI, 2010)

Automatic Identity Inference for Smart TVs. - Avneesh Singh Saluja; Frank Mokaya; Mariano Phielipp; Branislav Kveton (Lifelong Learning, 2011)

Goal-conditioned Imitation Learning. - Yiming Ding; Carlos Florensa; Pieter Abbeel; Mariano Phielipp (NeurIPS, 2019)

Motion2Vec: Semi-Supervised Representation Learning from Surgical Videos. - Ajay Kumar Tanwani; Pierre Sermanet; Andy Yan; Raghav Anand; Mariano Phielipp; Ken Goldberg (ICRA, 2020)

Instance-based Generalization in Reinforcement Learning. - Martín Bertrán; Natalia Martínez; Mariano Phielipp; Guillermo Sapiro (NeurIPS, 2020)

Minimizing Communication while Maximizing Performance in Multi-Agent Reinforcement Learning. - Varun Kumar Vijay; Hassam Sheikh; Somdeb Majumdar; Mariano Phielipp (CoRR, 2021)

Neuroevolution-enhanced multi-objective optimization for mixed-precision quantization. - Santiago Miret; Vui Seng Chua; Mattias Marder; Mariano Phielipp; Nilesh Jain; Somdeb Majumdar (GECCO, 2022)

Maximizing Ensemble Diversity in Deep Reinforcement Learning. - Hassam Sheikh; Mariano Phielipp; Ladislau Bölöni (ICLR, 2022)

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

AnyMorph: Learning Transferable Polices By Inferring Agent Morphology. - Brandon Trabucco; Mariano Phielipp; Glen Berseth (ICML, 2022)

Learning Intrinsic Symbolic Rewards in Reinforcement Learning. - Hassam Ullah Sheikh; Shauharda Khadka; Santiago Miret; Somdeb Majumdar; Mariano Phielipp (IJCNN, 2022)

Offline Policy Comparison with Confidence: Benchmarks and Baselines. - Anurag Koul; Mariano Phielipp; Alan Fern (CoRR, 2022)

Group SELFIES: A Robust Fragment-Based Molecular String Representation. - Austin H. Cheng; Andy Cai; Santiago Miret; Gustavo Malkomes; Mariano Phielipp; Alán Aspuru-Guzik (CoRR, 2022)

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 (CoRL, 2023)

Learning Sparse Control Tasks from Pixels by Latent Nearest-Neighbor-Guided Explorations. - Ruihan Zhao 001; Ufuk Topcu; Sandeep Chinchali; Mariano Phielipp (CoRR, 2023)

Pretraining Graph Neural Networks for Few-Shot Analog Circuit Modeling and Design. - Kourosh Hakhamaneshi; Marcel Nassar; Mariano Phielipp; Pieter Abbeel; Vladimir Stojanovic (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Accelerating Visual Sparse-Reward Learning with Latent Nearest-Demonstration-Guided Explorations. - Ruihan Zhao 001; Ufuk Topcu; Sandeep P. Chinchali; Mariano Phielipp (CoRL, 2024)

FloorSet - a VLSI Floorplanning Dataset with Design Constraints of Real-World SOCs. - Uday Mallappa; Hesham Mostafa; Mikhail Galkin 001; Mariano Phielipp; Somdeb Majumdar (ICCAD, 2024)

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

PARSAC: Fast, Human-quality Floorplanning for Modern SoCs with Complex Design Constraints. - Hesham Mostafa; Uday Mallappa; Mikhail Galkin 001; Mariano Phielipp; Somdeb Majumdar (CoRR, 2024)

Improved Silent Data Error Detection Through Test Optimization Using Reinforcement Learning. - Manu Shamsa; John D. Martin; Mariano Phielipp; Thiago Macieira; Loganathan Lingappan; Brad Kelly; David Lerner; Michael Tucknott; Ethan Hansen (IRPS, 2025)

Efficient Morphology-Aware Policy Transfer to New Embodiments. - Michael Przystupa; Hongyao Tang; Martin Jägersand; Santiago Miret; Mariano Phielipp; Matthew E. Taylor; Glen Berseth (CoRR, 2025)