no code implementations • 29 Mar 2024 • Zhiwen Fan, Wenyan Cong, Kairun Wen, Kevin Wang, Jian Zhang, Xinghao Ding, Danfei Xu, Boris Ivanovic, Marco Pavone, Georgios Pavlakos, Zhangyang Wang, Yue Wang
This pre-processing is usually conducted via a Structure-from-Motion (SfM) pipeline, a procedure that can be slow and unreliable, particularly in sparse-view scenarios with insufficient matched features for accurate reconstruction.
no code implementations • 29 Dec 2023 • Kevin Wang, Jason Ramos, Ramon Lawrence
With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors.
no code implementations • 28 Dec 2023 • Kaitlyn Wang, Jian Ge, Kevin Willis, Kevin Wang, Yinan Zhao
K01821. b is a sub-Earth with a radius of $0. 648R_\oplus$, orbiting a G dwarf over a 0. 91978-day period.
no code implementations • 4 Dec 2023 • Kaitlyn Wang, Jian Ge, Kevin Willis, Kevin Wang, Yinan Zhao
This paper presents GPFC, a novel Graphics Processing Unit (GPU) Phase Folding and Convolutional Neural Network (CNN) system to detect exoplanets using the transit method.
1 code implementation • 28 Nov 2023 • Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang
Recent advancements in real-time neural rendering using point-based techniques have paved the way for the widespread adoption of 3D representations.
no code implementations • 27 Nov 2023 • Kevin Wang, Seth Akins, Abdallah Mohammed, Ramon Lawrence
Generative AI systems such as ChatGPT have a disruptive effect on learning and assessment.
1 code implementation • 28 Apr 2023 • Wenqing Zheng, S P Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang
For a complicated algorithm, its implementation by a human programmer usually starts with outlining a rough control flow followed by iterative enrichments, eventually yielding carefully generated syntactic structures and variables in a hierarchy.
1 code implementation • 30 Dec 2022 • Wenqing Zheng, S P Sharan, Zhiwen Fan, Kevin Wang, Yihan Xi, Zhangyang Wang
Learning efficient and interpretable policies has been a challenging task in reinforcement learning (RL), particularly in the visual RL setting with complex scenes.
3 code implementations • 1 Nov 2022 • Kevin Wang, Alexandre Variengien, Arthur Conmy, Buck Shlegeris, Jacob Steinhardt
Research in mechanistic interpretability seeks to explain behaviors of machine learning models in terms of their internal components.
no code implementations • 13 Jul 2022 • Stephen Mcaleer, JB Lanier, Kevin Wang, Pierre Baldi, Roy Fox, Tuomas Sandholm
Instead of adding only deterministic best responses to the opponent's least exploitable population mixture, SP-PSRO also learns an approximately optimal stochastic policy and adds it to the population as well.
no code implementations • 19 Jan 2022 • Stephen Mcaleer, Kevin Wang, John Lanier, Marc Lanctot, Pierre Baldi, Tuomas Sandholm, Roy Fox
PSRO is based on the tabular double oracle (DO) method, an algorithm that is guaranteed to converge to a Nash equilibrium, but may increase exploitability from one iteration to the next.
Multi-agent Reinforcement Learning reinforcement-learning +2
no code implementations • 31 Mar 2021 • Kevin Wang, Deva Ramanan, Aayush Bansal
Associating latent codes of a video and manifold projection enables users to make desired edits.
1 code implementation • NeurIPS 2021 • Stephen Mcaleer, John Lanier, Kevin Wang, Pierre Baldi, Roy Fox
NXDO is the first deep RL method that can find an approximate Nash equilibrium in high-dimensional continuous-action sequential games.
no code implementations • 20 Sep 2017 • Ramon Iglesias, Federico Rossi, Kevin Wang, David Hallac, Jure Leskovec, Marco Pavone
The goal of this paper is to present an end-to-end, data-driven framework to control Autonomous Mobility-on-Demand systems (AMoD, i. e. fleets of self-driving vehicles).
Robotics Multiagent Systems Systems and Control Applications