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Journal Articles
- 2024
[j2]Jed A. Duersch
, Tommie A. Catanach, Niladri Das:
Logical activation functions for training arbitrary probabilistic Boolean operations. Inf. Sci. 664: 120304 (2024)- 2020
- [j1]Jed A. Duersch, Thomas A. Catanach:
Generalizing Information to the Evolution of Rational Belief. Entropy 22(1): 108 (2020)
Conference and Workshop Papers
- 2023
- [c2]Tommie A. Catanach, Niladri Das:
Metrics for Bayesian Optimal Experiment Design Under Model Misspecification. CDC 2023: 7707-7714 - 2022
- [c1]Niladri Das, Jed A. Duersch, Tommie A. Catanach:
Variational Kalman Filtering with H∞-Based Correction for Robust Bayesian Learning in High Dimensions. CDC 2022: 7522-7528
Informal and Other Publications
- 2024
- [i11]Shijie Zhong, Wanggang Shen, Tommie A. Catanach, Xun Huan:
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo. CoRR abs/2403.18072 (2024) - [i10]Niladri Das, Ross Guttromson, Tommie A. Catanach:
Development of Bayesian Component Failure Models in E1 HEMP Grid Analysis. CoRR abs/2406.01923 (2024) - [i9]Jake Callahan, Kevin Monogue, Rubén Villarreal, Thomas A. Catanach:
Analysis and Optimization of Seismic Monitoring Networks with Bayesian Optimal Experiment Design. CoRR abs/2410.07215 (2024) - [i8]Jed A. Duersch, Tommie A. Catanach, Alexander Safonov, Jeremy Wendt:
Curvature in the Looking-Glass: Optimal Methods to Exploit Curvature of Expectation in the Loss Landscape. CoRR abs/2411.16914 (2024) - 2023
- [i7]Tommie A. Catanach, Niladri Das:
Metrics for Bayesian Optimal Experiment Design under Model Misspecification. CoRR abs/2304.07949 (2023) - [i6]Daniel Hothem, Kevin C. Young, Tommie A. Catanach, Timothy Proctor:
Learning a quantum computer's capability using convolutional neural networks. CoRR abs/2304.10650 (2023) - 2022
- [i5]Jed A. Duersch, Thomas A. Catanach, Niladri Das:
Adaptive n-ary Activation Functions for Probabilistic Boolean Logic. CoRR abs/2203.08977 (2022) - [i4]Niladri Das, Jed A. Duersch, Thomas A. Catanach:
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions. CoRR abs/2204.13089 (2022) - [i3]Rubén Villarreal, Nikolaos N. Vlassis, Nhon N. Phan, Tommie A. Catanach, Reese E. Jones, Nathaniel A. Trask, Sharlotte L. B. Kramer, WaiChing Sun:
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter. CoRR abs/2209.13126 (2022) - 2021
- [i2]Jed A. Duersch, Thomas A. Catanach:
Parsimonious Inference. CoRR abs/2103.02165 (2021) - 2019
- [i1]Jed A. Duersch, Thomas A. Catanach:
Generalizing Information to the Evolution of Rational Belief. CoRR abs/1911.09559 (2019)
Coauthor Index
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