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Articles: 2'379'978
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01 October 2023
 
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Results 1 to 20 of 57 for query "Jeff Schneider". (0.00 sec.)

[    1    2    3    ]   Next
1.
Non-Parametric Inference in Astrophysics
Larry Wasserman; Christopher J. Miller; Robert C. Nichol; Chris Genovese; Woncheol Jang; Andrew J. Connolly; Andrew W. Moore; Jeff Schneider; the PICA group;
3 Dec 2001
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2.
Fast Algorithms and Efficient Statistics: N-point Correlation Functions
Andrew Moore; Andy Connolly; Chris Genovese; Alex Gray; Larry Grone; Nick Kanidoris II; Robert Nichol; Jeff Schneider; Alex Szalay; Istvan Szapudi; Larry Wasserman;
14 Dec 2000
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3.
Near-optimal Policy Identification in Active Reinforcement Learning
Xiang Li; Viraj Mehta; Johannes Kirschner; Ian Char; Willie Neiswanger; Jeff Schneider; Andreas Krause; Ilija Bogunovic;
19 Dec 2022
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4.
Exploration via Planning for Information about the Optimal Trajectory
Viraj Mehta; Ian Char; Joseph Abbate; Rory Conlin; Mark D. Boyer; Stefano Ermon; Jeff Schneider; Willie Neiswanger;
6 Oct 2022
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5.
Cost Aware Asynchronous Multi-Agent Active Search
Arundhati Banerjee; Ramina Ghods; Jeff Schneider;
5 Oct 2022
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6.
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning
Adam Villaflor; Zhe Huang; Swapnil Pande; John Dolan; Jeff Schneider;
21 Jul 2022
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7.
How Useful are Gradients for OOD Detection Really?
Conor Igoe; Youngseog Chung; Ian Char; Jeff Schneider;
20 May 2022
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8.
Multi-Agent Active Search using Detection and Location Uncertainty
Arundhati Banerjee; Ramina Ghods; Jeff Schneider;
9 Mar 2022
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9.
UGV-UAV Object Geolocation in Unstructured Environments
David Guttendorf; D.W. Wilson Hamilton; Anne Harris Heckman; Herman Herman; Felix Jonathan; Prasanna Kannappan; Nicholas Mireles; Luis Navarro-Serment; Jean Oh; Wei Pu; Rohan Saxena; Jeff Schneider; Matt Schnur; Carter Tiernan; Trenton Tabor;
14 Jan 2022
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10.
Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling
Benjamin Freed; Aditya Kapoor; Ian Abraham; Jeff Schneider; Howie Choset;
23 Dec 2021
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11.
An Experimental Design Perspective on Model-Based Reinforcement Learning
Viraj Mehta; Biswajit Paria; Jeff Schneider; Stefano Ermon; Willie Neiswanger;
10 Dec 2021
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12.
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification
Youngseog Chung; Ian Char; Han Guo; Jeff Schneider; Willie Neiswanger;
21 Sep 2021
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13.
SBEVNet: End-to-End Deep Stereo Layout Estimation
Divam Gupta; Wei Pu; Trenton Tabor; Jeff Schneider;
25 May 2021
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14.
Computational catalyst discovery: Active classification through myopic multiscale sampling
Kevin Tran; Willie Neiswanger; Kirby Broderick; Erix Xing; Jeff Schneider; Zachary W. Ulissi;
2 Feb 2021
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15.
Affordance-based Reinforcement Learning for Urban Driving
Tanmay Agarwal; Hitesh Arora; Jeff Schneider;
15 Jan 2021
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16.
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
Youngseog Chung; Willie Neiswanger; Ian Char; Jeff Schneider;
19 Nov 2020
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17.
Multi-Agent Active Search using Realistic Depth-Aware Noise Model
Ramina Ghods; William J. Durkin; Jeff Schneider;
10 Nov 2020
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18.
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning
Zhiqian Qiao; Jeff Schneider; John M. Dolan;
9 Nov 2020
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19.
Interactive Visualization for Debugging RL
Shuby Deshpande; Benjamin Eysenbach; Jeff Schneider;
14 Aug 2020
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20.
Vizarel: A System to Help Better Understand RL Agents
Shuby Deshpande; Jeff Schneider;
10 Jul 2020
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