Daniel D. Lee

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 110

Top Venues

Publications

Patrick Cook, Danny Jammooa, Morten Hjorth-Jensen, Daniel D. Lee, Dean Lee
Parametric Matrix Models. CoRR (2024)
Chanwoo Chun, Daniel D. Lee
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks. CoRR (2023)
Travers Rhodes, Daniel D. Lee
TimewarpVAE: Simultaneous Time-Warping and Representation Learning of Trajectories. CoRR (2023)
Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler
EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks. CoRR (2023)
Siddharth Rupavatharam, Xiaoran Fan, Caleb Escobedo, Daewon Lee, Larry D. Jackel, Richard E. Howard, Colin Prepscius, Daniel D. Lee, Volkan Isler
AmbiSense: Acoustic Field Based Blindspot-Free Proximity Detection and Bearing Estimation. IROS (2023)
Niko A. Grupen, Michael Hanlon, Alexis Hao, Daniel D. Lee, Bart Selman
Policy-Value Alignment and Robustness in Search-based Multi-Agent Learning. CoRR (2023)
Weishun Zhong, Ben Sorscher, Daniel D. Lee, Haim Sompolinsky
A theory of learning with constrained weight-distribution. CoRR (2022)
Travers Rhodes, Tapomayukh Bhattacharjee, Daniel D. Lee
Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE). IROS (2022)
J. Jon Ryu, Shouvik Ganguly, Younghan Kim, Yung-Kyun Noh, Daniel D. Lee
Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Trans. Inf. Theory 68 (6) (2022)
Nikhil Chavan Dafle, Sergiy Popovych, Shubham Agrawal, Daniel D. Lee, Volkan Isler
Simultaneous Object Reconstruction and Grasp Prediction using a Camera-centric Object Shell Representation. IROS (2022)
Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler
EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks. IEEE Robotics Autom. Lett. 7 (4) (2022)
Niko A. Grupen, Bart Selman, Daniel D. Lee
Cooperative Multi-Agent Fairness and Equivariant Policies. AAAI (2022)
Niko A. Grupen, Daniel D. Lee, Bart Selman
Multi-Agent Curricula and Emergent Implicit Signaling. AAMAS (2022)
Xiaoran Fan, Riley Simmons-Edler, Daewon Lee, Larry D. Jackel, Richard E. Howard, Daniel D. Lee
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection. CoRR (2021)
Jinwook Huh, Daniel D. Lee, Volkan Isler
Learning Continuous Cost-to-Go Functions for Non-holonomic Systems. CoRR (2021)
Travers Rhodes, Daniel D. Lee
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization. NeurIPS (2021)
Niko A. Grupen, Daniel D. Lee, Bart Selman
Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork. CoRR (2021)
Xiaoran Fan, Riley Simmons-Edler, Daewon Lee, Larry D. Jackel, Richard E. Howard, Daniel D. Lee
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection. IROS (2021)
Jinwook Huh, Volkan Isler, Daniel D. Lee
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning. ICRA (2021)
Nikhil Chavan Dafle, Sergiy Popovych, Shubham Agrawal, Daniel D. Lee, Volkan Isler
Object Shell Reconstruction: Camera-centric Object Representation for Robotic Grasping. CoRR (2021)
Ziyun Wang, Eric A. Mitchell, Volkan Isler, Daniel D. Lee
Geodesic-HOF: 3D Reconstruction Without Cutting Corners. AAAI (2021)
Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas
Deep Reinforcement Learning for Active Target Tracking. ICRA (2021)
Jinwook Huh, Daniel D. Lee, Volkan Isler
Learning Continuous Cost-to-Go Functions for Non-holonomic Systems. IROS (2021)
Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors. ICRA (2021)
Travers Rhodes, Daniel D. Lee
Regularization. CoRR (2021)
Yuan Chen, Colin Prepscius, Daewon Lee, Daniel D. Lee
Tactile Velocity Estimation for Controlled In-Grasp Sliding. IEEE Robotics Autom. Lett. 6 (2) (2021)
Daniel Yang, Tarik Tosun, Benjamin Eisner, Volkan Isler, Daniel D. Lee
Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction. ICRA (2021)
Minghan Wei, Daewon Lee, Volkan Isler, Daniel D. Lee
Occupancy Map Inpainting for Online Robot Navigation. ICRA (2021)
Niko A. Grupen, Bart Selman, Daniel D. Lee
Fairness for Cooperative Multi-Agent Learning with Equivariant Policies. CoRR (2021)
Ziyun Wang, Eric A. Mitchell, Volkan Isler, Daniel D. Lee
Geodesic-HOF: 3D Reconstruction Without Cutting Corners. CoRR (2020)
Daniel R. Kepple, Daewon Lee, Colin Prepsius, Volkan Isler, Il Memming Park, Daniel D. Lee
Jointly Learning Visual Motion and Confidence from Local Patches in Event Cameras. ECCV (6) (2020)
Ziyun Wang, Volkan Isler, Daniel D. Lee
Surface Hof: Surface Reconstruction From A Single Image Using Higher Order Function Networks. ICIP (2020)
Eric Mitchell, Selim Engin, Volkan Isler, Daniel D. Lee
Higher-Order Function Networks for Learning Composable 3D Object Representations. ICLR (2020)
Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee
Higher Order Function Networks for View Planning and Multi-View Reconstruction. ICRA (2020)
Tarik Tosun, Daniel Yang, Ben Eisner, Volkan Isler, Daniel D. Lee
Robotic Grasping through Combined image-Based Grasp Proposal and 3D Reconstruction. CoRR (2020)
Jinwook Huh, Galen Xing, Ziyun Wang, Volkan Isler, Daniel D. Lee
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning. CoRR (2020)
Jinwook Huh, Galen Xing, Ziyun Wang, Volkan Isler, Daniel D. Lee
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning. ISER (2020)
Xiaoran Fan, Daewon Lee, Yuan Chen, Colin Prepscius, Volkan Isler, Larry D. Jackel, H. Sebastian Seung, Daniel D. Lee
Acoustic Collision Detection and Localization for Robot Manipulators. IROS (2020)
Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas
Learning to Track Dynamic Targets in Partially Known Environments. CoRR (2020)
Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee
Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection. CoRR (2020)
Niko A. Grupen, Daniel D. Lee, Bart Selman
Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems. CoRR (2020)
Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
Reward Prediction Error as an Exploration Objective in Deep RL. IJCAI (2020)
Fernando Cladera Ojeda, Anthony Bisulco, Daniel R. Kepple, Volkan Isler, Daniel D. Lee
On-Device Event Filtering with Binary Neural Networks for Pedestrian Detection Using Neuromorphic Vision Sensors. ICIP (2020)
Jinwook Huh, Volkan Isler, Daniel D. Lee
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning. CoRR (2020)
Anthony Bisulco, Fernando Cladera Ojeda, Volkan Isler, Daniel D. Lee
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors. CoRR (2020)
Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas
Learning Q-network for Active Information Acquisition. CoRR (2019)
Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. CoRR (2019)
Kanghoon Lee, Geon-hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim
Bayesian optimistic Kullback-Leibler exploration. Mach. Learn. 108 (5) (2019)
Selim Engin, Eric Mitchell, Daewon Lee, Volkan Isler, Daniel D. Lee
Higher Order Function Networks for View Planning and Multi-View Reconstruction. CoRR (2019)
Ziyun Wang, Volkan Isler, Daniel D. Lee
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks. CoRR (2019)
Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
QXplore: Q-learning Exploration by Maximizing Temporal Difference Error. CoRR (2019)
Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas
Learning Q-network for Active Information Acquisition. IROS (2019)
Heejin Jeong, Clark Zhang, George J. Pappas, Daniel D. Lee
Assumed Density Filtering Q-learning. IJCAI (2019)
Bhoram Lee, Clark Zhang, Zonghao Huang, Daniel D. Lee
Online Continuous Mapping using Gaussian Process Implicit Surfaces. ICRA (2019)
Riley Simmons-Edler, Ben Eisner, Eric Mitchell, H. Sebastian Seung, Daniel D. Lee
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies. CoRR (2019)
Jinwook Huh, Ömür Arslan, Daniel D. Lee
Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. ISRR (2019)
Jinwook Huh, Omur Arslan, Daniel D. Lee
Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning. CoRR (2019)
Minoru Asada, Peter Stone, Manuela Veloso, Daniel D. Lee, Daniele Nardi
RoboCup: A Treasure Trove of Rich Diversity for Research Issues and Interdisciplinary Connections [TC Spotlight]. IEEE Robotics Autom. Mag. 26 (3) (2019)
Eric Mitchell, Kazim Selim Engin, Volkan Isler, Daniel D. Lee
Higher-Order Function Networks for Learning Composable 3D Object Representations. CoRR (2019)
Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro
Learning Optimal Resource Allocations in Wireless Systems. IEEE Trans. Signal Process. 67 (10) (2019)
Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro
Dual Domain Learning of Optimal Resource Allocations in Wireless Systems. ICASSP (2019)
Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh, Bhoram Lee, Daewon Lee, Volkan Isler, H. Sebastian Seung, Daniel D. Lee
Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a Planner. IROS (2019)
Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee
Memory Augmented Control Networks. ICLR (Poster) (2018)
Christopher W. Lynn, Daniel D. Lee
Maximizing Activity in Ising Networks via the TAP Approximation. AAAI (2018)
Heejin Jeong, Daniel D. Lee
Bayesian Q-learning with Assumed Density Filtering. AAAI Spring Symposia (2018)
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. 30 (7) (2018)
Arbaaz Khan, Clark Zhang, Daniel D. Lee, Vijay Kumar, Alejandro Ribeiro
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients. CoRR (2018)
Clark Zhang, Jinwook Huh, Daniel D. Lee
Learning Implicit Sampling Distributions for Motion Planning. CoRR (2018)
Ty Nguyen, Tolga Özaslan, Ian D. Miller, James Keller, Giuseppe Loianno, Camillo J. Taylor, Daniel D. Lee, Vijay Kumar, Joseph H. Harwood, Jennifer M. Wozencraft
U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification. CoRR (2018)
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
Generative Local Metric Learning for Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. 40 (1) (2018)
Christopher W. Lynn, Daniel D. Lee
Maximizing Activity in Ising Networks via the TAP Approximation. CoRR (2018)
Steven W. Chen, Kelsey Saulnier, Nikolay Atanasov, Daniel D. Lee, Vijay Kumar, George J. Pappas, Manfred Morari
Approximating Explicit Model Predictive Control Using Constrained Neural Networks. ACC (2018)
SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee
Learning Data Manifolds with a Cutting Plane Method. Neural Comput. 30 (10) (2018)
Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, Danielle S. Bassett
Surges of collective human activity emerge from simple pairwise correlations. CoRR (2018)
Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro
Learning Optimal Resource Allocations in Wireless Systems. CoRR (2018)
Marcell Missura, Daniel D. Lee, Maren Bennewitz
Minimal Construct: Efficient Shortest Path Finding for Mobile Robots in Polygonal Maps. IROS (2018)
Shouvik Ganguly, Jongha Ryu, Young-Han Kim, Yung-Kyun Noh, Daniel D. Lee
Nearest neighbor density functional estimation based on inverse Laplace transform. CoRR (2018)
Jinwook Huh, Bhoram Lee, Daniel D. Lee
Constrained Sampling-Based Planning for Grasping and Manipulation. ICRA (2018)
Jinwook Huh, Daniel D. Lee
Efficient Sampling With Q-Learning to Guide Rapidly Exploring Random Trees. IEEE Robotics Autom. Lett. 3 (4) (2018)
Mark Eisen, Clark Zhang, Luiz F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro
Online Deep Learning in Wireless Communication Systems. ACSSC (2018)
Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee
Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40 (1) (2018)
Clark Zhang, Jinwook Huh, Daniel D. Lee
Learning Implicit Sampling Distributions for Motion Planning. IROS (2018)
Xiang Deng, Daniel D. Lee
Artificial Invariant Subspace for Humanoid Robot Balancing in Locomotion. IROS (2018)
Steven W. Chen, Nikolay Atanasov, Arbaaz Khan, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar
Neural Network Memory Architectures for Autonomous Robot Navigation. CoRR (2017)
Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar
End-to-End Navigation in Unknown Environments using Neural Networks. CoRR (2017)
Marcell Missura, Daniel D. Lee, Oskar von Stryk, Maren Bennewitz
The synchronized holonomic model: A framework for efficient generation of motion. IROS (2017)
Bhoram Lee, Daniel D. Lee
Self-supervised online learning of appearance for 3D tracking. IROS (2017)
Heejin Jeong, Daniel D. Lee
Bayesian Q-learning with Assumed Density Filtering. CoRR (2017)
Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee
Memory Augmented Control Networks. CoRR (2017)
Stephen G. McGill, Seung-Joon Yi, Hak Yi, Min Sung Ahn, Sanghyun Cho, Kevin Liu, Daniel Sun, Bhoram Lee, Heejin Jeong, Jinwook Huh, Dennis W. Hong, Daniel D. Lee
Team THOR's Entry in the DARPA Robotics Challenge Finals 2015. J. Field Robotics 34 (4) (2017)
Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee
Generative Local Metric Learning for Kernel Regression. NIPS (2017)
Xiang Deng, Fei Miao, Daniel D. Lee
Artificial invariant subspace with potential functions for humanoid robot balancing. IROS (2017)
SueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee
Learning Data Manifolds with a Cutting Plane Method. CoRR (2017)
SueYeon Chung, Daniel D. Lee, Haim Sompolinsky
Classification and Geometry of General Perceptual Manifolds. CoRR (2017)
Jinwook Huh, Bhoram Lee, Daniel D. Lee
Adaptive motion planning with high-dimensional mixture models. ICRA (2017)
Seung-Joon Yi, Daniel D. Lee
Dynamic heel-strike toe-off walking controller for full-size modular humanoid robots. Humanoids (2016)
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI (2016)
Seung-Joon Yi, Daniel D. Lee
Heel and toe lifting walk controller for resource constrained humanoid robots. IROS (2016)
Yongbo Qian, Daniel D. Lee
Adaptive Field Detection and Localization in Robot Soccer. RoboCup (2016)
Bhoram Lee, Daniel D. Lee
Learning anisotropic ICP (LA-ICP) for robust and efficient 3D registration. ICRA (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Daniel D. Lee