Country
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten, Jouni Helske, Matti Vihola
Neural Information Processing Systems http://nips.cc/
Wasserstein Weisfeiler-Lehman Graph Kernels
Matteo Togninalli, Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten Borgwardt
Neural Information Processing Systems http://nips.cc/
Large Language Models Can Implement Policy Iteration Ethan Brooks 1, Logan Walls 2, Richard L. Lewis
Gradient techniques are inherently slow, sacrificing the "few-shot" quality
Robust Principal Component Analysis with Adaptive Neighbors
Additionally, the framework is further applied to PCA problem to demonstrate the superiority and effectiveness of the proposedRWL-ANmodel.
Constrained Cross-Entropy Method for Safe Reinforcement Learning
Neural Information Processing Systems http://nips.cc/
JAWS: Auditing Predictive Uncertainty Under Covariate Shift
Given Assumptions 1-4 in Giordanoetal.
Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming
Fei Wang, James Decker, Xilun Wu, Gregory Essertel, Tiark Rompf
In this paper we propose an implementation of backpropagation using functions with callbacks, where the forward pass is executed as a sequence of function calls, and the backward pass as a corresponding sequence of function returns. A key realization is that this technique of chaining callbacks is well known in the programming languages community as continuation-passing style (CPS) .