7 citations · 7 across the 4 of their papers we have counts for
4 papers
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions
Niladri Das, Jed A. Duersch, Thomas A. Catanach
In this paper, we address the problem of convergence of sequential variational inference filter (VIF) through the application of a robust variational objective and Hinf-norm based…
Adaptive n-ary Activation Functions for Probabilistic Boolean Logic
Jed A. Duersch, Thomas A. Catanach, Niladri Das
Balancing model complexity against the information contained in observed data is the central challenge to learning. In order for complexity-efficient models to exist and be discove…
Parsimonious Inference
Jed A. Duersch, Thomas A. Catanach
Bayesian inference provides a uniquely rigorous approach to obtain principled justification for uncertainty in predictions, yet it is difficult to articulate suitably general prior…
Generalizing Information to the Evolution of Rational Belief
Jed A. Duersch, Thomas A. Catanach
Information theory provides a mathematical foundation to measure uncertainty in belief. Belief is represented by a probability distribution that captures our understanding of an ou…