Ben Eisner

Hello! I'm a 5th-Year Ph.D. student in the Robotics Institute at Carnegie Mellon University, working with Prof. David Held. I work on 3D geometric reasoning for robotic manipulation. My research is supported in part by the NSF Graduate Research Fellowship.

Here's my cv, my Google Scholar profile, and my Github profile.

You can reach me at ben.a.eisner@gmail.com.

Publications

Non-rigid Relative Placement through 3D Dense Diffusion Non-rigid Relative Placement through 3D Dense Diffusion
Eric Cai, Octavian Donca, Ben Eisner, David Held
CoRL 2024
paper | website | code
FlowbotHD: History-Aware Diffuser Handling Ambiguities in Articulated Objects Manipulation FlowbotHD: History-Aware Diffuser Handling Ambiguities in Articulated Objects Manipulation
Yishu Li, Wen Hui Leng, Yiming Fang, Ben Eisner, David Held
CoRL 2024
paper | website | code
Sequential Object-Centric Relative Placement Prediction for Long-horizon Imitation Learning Sequential Object-Centric Relative Placement Prediction for Long-horizon Imitation Learning
Ben Eisner, Eric Cai, Octavian Donca, Teeratham Vitchutripop, David Held
Workshop on Learning Effective Abstractions for Planning (LEAP) @ CoRL 2024
paper | website | code
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik, Jonathan Scholz, David Held
International Conference on Learning Representations (ICLR) 2024
paper | website | code
FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection
Harry Zhang, Ben Eisner, David Held
CoRL 2023
paper | website | code
On Time-Indexing as Inductive Bias in Deep RL for Sequential Manipulation Tasks On Time-Indexing as Inductive Bias in Deep RL for Sequential Manipulation Tasks
M. Nomaan Qureshi, Ben Eisner, David Held
Learning Meets Model-based Methods for Manipulation and Grasping Workshop @ IROS 2023
paper
TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation
Chuer Pan, Brian Okorn, Harry Zhang, Ben Eisner, David Held
CoRL 2022
paper | website | code
FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objects FlowBot3D: Learning 3D Articulation Flow to Manipulate Articulated Objects
Ben Eisner, Harry Zhang, David Held
RSS 2022, Best Paper Finalist
paper | website | code | talk
Deep Sequenced Linear Dynamical Systems for Manipulation Policy Learning Deep Sequenced Linear Dynamical Systems for Manipulation Policy Learning
M. Nomaan Qureshi, Ben Eisner, David Held
ICLR 2022 Workshop on Generalizable Policy Learning in Physical World
paper | website | code
Self-supervised Transparent Liquid Segmentation for Robotic Pouring Self-supervised Transparent Liquid Segmentation for Robotic Pouring
Gautham Narasimhan, Kai Zhang, Ben Eisner, Xingyu Lin, David Held
ICRA 2022
paper | website | code
Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction
Daniel Yang, Tarik Tosun, Ben Eisner, Volkan Isler, Daniel Lee
ICRA 2021
paper
Reward Prediction Error as an Exploration Objective in Deep RL Reward Prediction Error as an Exploration Objective in Deep RL
Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee
IJCAI 2020
paper
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner
Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, Sebastian Seung, Daniel Lee
IROS 2019
paper
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies Q-Learning for Continuous Actions with Cross-Entropy Guided Policies
Riley Simmons-Edler, Ben Eisner, Eric Mitchell, Sebastian Seung, Daniel Lee
ICML 2019 Workshop on RL4RealLife
paper
Deep Learning Methods for 3D Segmentation of Neural Tissue in EM Images Deep Learning Methods for 3D Segmentation of Neural Tissue in EM Images
Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee
Princeton University Senior Thesis
paper | code
emoji2vec: Learning emoji representations from their description emoji2vec: Learning emoji representations from their description
Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko Bošnjak, Sebastian Riedel
Best Paper atEMNLP 2016 Workshop on SocialNLP
paper | code