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2024

Talk Speaker
Toward Full-Stack Reliable Robot Learning for Autonomy and Interaction [abstract][recording] Glen Chou
Deep Reinforcement Learning for Multi-Agent Interaction [abstract][recording] Stefano V. Albrecht
Object-level Planning: Bridging the Gap between Human Knowledge and Task and Motion Planning [abstract][recording] David Paulius
[internal] Lishuo, David, Shane, Ivy, Lakshita [recording]
[internal] Benedict Quartey, Thao Nguyen [recording][slides: 1 2]
Towards Interactive Task and Motion Imitation [abstract][recording] Felix Yanwei Wang
Towards Composable Scene Representations in Robotics and Vision [abstract][recording] Ondrej Biza
[internal] Ziyi, Benned, Ben, Arjun, Mingxi [recording][slides: 1 2 3 4 5]
[internal] Sam Lobel, Rafael Rodriguez-Sanchez [recording][slides: 1 2]
Building General-Purpose Robots with Integrated Learning and Planning [abstract][recording] Jiayuan Mao
[internal] Anita, Tuluhan, Tabby, Sergio, Haotian, Prof. Matthew Stein's Group [recording]
[internal] Alper Ahmetoglu, Eric Ewing [recording]
[internal] A few attempts to learn generalizable manipulation skills - An imitation learning view[abstract][recording]Mingxi Jia

2023

Talk Speaker
Regularization in Neural Networks: A Probabilistic Perspective [abstract][recording] Tim Rudner
Broadening Robot Dexterity: Leveraging Elements in Manipulation Task Environments [abstract][recording] Xianyi Cheng
The Hessian Perspective into the Nature of Neural Networks [abstract][recording] Sidak Pal Singh
Quasimetric Reinforcement Learning [abstract][recording] Tongzhou Wang
Generalizing Beyond Your Data through Compositional Energy Functions [abstract][recording] Yilun Du
A2Perf: Benchmarking Autonomous Agents for the Real World [abstract][recording] Ike Uchendu
Towards Social Autotelic Agents: Open-Ended Skill Learning with Goals, Language and Intrinsically Motivated Reinforcement Learning [abstract][recording] Cédric Colas
Natural Language Task Specification for Robots [abstract][recording] Jason Liu
Deep Symbol Generation and Rule Learning [abstract][recording] Alper Ahmetoglu
Pragmatic, Uncertainty Guided Reinforcement Learning [abstract][recording] Taylor Killian
Grounded Understanding of Actions and Language via Bayesian Inverse Planning [abstract][recording] Tan Zhi-Xuan
Improving Unsupervised Visual Program Inference with Code Rewriting Families [abstract][recording] Aditya Ganeshan
Inventing Plannable Abstractions from Demonstrations [abstract][recording] Nishanth Kumar
Equivariant Learning for Robotic Manipulation [abstract][recording] Dian Wang
Scaling Goal-based Exploration via Pruning Proto-goals [abstract] & Learning with Program Induction [abstract][recording] Akhil Bagaria & Skye Thompson
Open and Efficient Reinforcement Learning from Human Feedback [abstract][recording] Louis Catricato
The Uninteded Consequences of Discount Regularization [recording] Sarah Rathnam
Interpretable Artificial Intelligence for Personalized Human-Robot Collaboration [recording] Rohan Paleja
Choreorobotics: An Emerging Discipline [abstract][recording] Catie Cuan

2022

Talk Speaker
Handling Distribution Shifts by training RL agents to be adaptive [abstract][recording] Anurag Ajay
Resource Optimization for Learning in Robotics [abstract][recording] Shivam Vats
Towards understanding self-supervised representation learning [abstract][recording] Nikunj Saunshi
Integrating Psychophysiological Measurements with Robotics in Dynamic Environments [abstract][recording] Pooja Bovard And Courtney Tse
Learning and Memory in General Decision Processes [abstract][recording] Cam Allen
Creating Versatile Learning Agents Via Lifelong Compositionality [abstract][recording] Jorge Mendez
Learning Scalable Strategies for Swarm Robotic Systems [abstract][recording] Lishuo Pan
Dynamic probabilistic logic models for effective task-specific abstractions in RL [abstract][recording] Harsha Kokel
Why is this Taking so Dang Long? The Performance Characteristics of Multi-agent Path Finding Algorithms [abstract][recording] Eric Ewing
Learning-Augmented Anticipatory Planning: designing capable and trustworthy robots that plan despite missing knowledge [abstract][recording] Gregory Stein
Towards Lifelong Reinforcement Learning through Zero-Shot Logical Composition [abstract][recording] Geraud Nangue Tasse
WHAT IS ARiSE AND ITS PURPOSE, HOW DOES IT BENEFIT HAMPTON UNIVERSITY, LOCAL MILITARY/GOVERNMENT AGENCIES, UAS INDUSTRIES, AND THE COMMUNITIES OF HAMPTON ROADS [abstract][recording] John P Murray
Learning and Using Hierarchical Abstractions for Efficient Taskable Robots [abstract][recording] Naman Shah
Representation in Robotics [abstract][recording] Kaiyu Zheng
Toward More Robust Hyperparameter Optimization [abstract][recording] A. Feder Cooper
Statistical and Computational Issues in Reinforcement Learning (with Linear Function Approximation) [abstract][recording] Gaurav Mahajan
On the Expressivity of Markov Reward [abstract][recording] Dave Abel
Robot Skill Learning via Representation Sharing and Reward Conditioning[abstract] & Shape-Based Transfer of Generic Skills [abstract][recording] Tuluhan Akbulut & Skye Thompson
Hardware Architecture for LiDAR Point Cloud Processing in Autonomous Driving [abstract][recording] Xinming Huang
Working with Spot [abstract] & Count based exploration [abstract][recording] Kaiyu Zheng & Max Merlin & Sam Lobel
MICo: Improved representations via sampling-based state similarity for Markov decision processes [abstract][recording] Pablo Samuel Castro
Weak inductive biases for composable primitive representations [abstract][recording] Wilka Carvalho
Mirror Descent Policy Optimization [abstract][recording] Manan Tomar
Joint Task and Motion Planning with the Functional Object-Oriented Network [abstract][recording] David Paulius