A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Gradient-guided nested sampling improves posterior inference efficiency.
Recent breakthroughs in defenses against adversarial examples, like adversarial training, make the neural networks robust against various classes of attackers (e.g., first-order gradient-based attacks). However, it is an open question whether the adversarially trained networks are truly robust under unknown attacks. In…
Paper proposes an alternative to set losses for predicting unordered variables without imposing structure.
Gradient guidance improves diffusion models for optimizing specific objectives.
GGFPS improves model performance by sampling molecules more efficiently.
New method corrects bias in stochastic gradient samplers.
Natural images are virtually surrounded by low-density misclassified regions that can be efficiently discovered by gradient-guided search --- enabling the generation of adversarial images. While many techniques for detecting these attacks have been proposed, they are easily bypassed when the adversary has full knowledg…
RLD improves combinatorial optimization by avoiding local minima.
Graph Energy Matching improves generation quality for molecular graphs.
MI-GAN solves OPF with renewable uncertainty using model-informed layers.