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Investigating Sindy As a Tool For Causal Discovery In Time Series Signals


Dec 29, 2022
Andrew O'Brien, Rosina Weber, Edward Kim

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MobilePTX: Sparse Coding for Pneumothorax Detection Given Limited Training Examples


Dec 08, 2022
Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, Christopher J. MacLellan

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* IAAI 2023 (7 pages) 

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Dictionary Learning with Accumulator Neurons


May 30, 2022
Gavin Parpart, Carlos Gonzalez, Terrence C. Stewart, Edward Kim, Jocelyn Rego, Andrew O'Brien, Steven Nesbit, Garrett T. Kenyon, Yijing Watkins

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EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting


Apr 14, 2022
Ethan Jacob Moyer, Alisha Isabelle Augustin, Satvik Tripathi, Ansh Aashish Dholakia, Andy Nguyen, Isamu Mclean Isozaki, Daniel Schwartz, Edward Kim

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* 5 pages, 2 figures, 2 tables 

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Perception Over Time: Temporal Dynamics for Robust Image Understanding


Mar 11, 2022
Maryam Daniali, Edward Kim

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Querying Labelled Data with Scenario Programs for Sim-to-Real Validation


Dec 01, 2021
Edward Kim, Jay Shenoy, Sebastian Junges, Daniel Fremont, Alberto Sangiovanni-Vincentelli, Sanjit Seshia

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* pre-print 

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A Scenario-Based Platform for Testing Autonomous Vehicle Behavior Prediction Models in Simulation


Nov 14, 2021
Francis Indaheng, Edward Kim, Kesav Viswanadha, Jay Shenoy, Jinkyu Kim, Daniel J. Fremont, Sanjit A. Seshia

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* Accepted to the NeurIPS 2021 Workshop on Machine Learning for Autonomous Driving 

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Multi-Agent Algorithmic Recourse


Oct 01, 2021
Andrew O'Brien, Edward Kim

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* Preliminary workshop version; work in progress 

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Addressing the IEEE AV Test Challenge with Scenic and VerifAI


Aug 20, 2021
Kesav Viswanadha, Francis Indaheng, Justin Wong, Edward Kim, Ellen Kalvan, Yash Pant, Daniel J. Fremont, Sanjit A. Seshia

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* Accepted to the IEEE AITest Conference 2021 

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