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.
New BGs use diffusion models to improve sampling from complex distributions.
Improved DL models robust against adversarial attacks for wireless signal classification.
CNN improves AMC accuracy under multipath fading channels.
Optimized CNNs for AMC on edge devices reduce complexity without sacrificing accuracy.
Automatic modulation classification (AMC) is an important task for modern communication systems; however, it is a challenging problem when signal features and precise models for generating each modulation may be unknown. We present a new biologically-inspired AMC method without the need for models or manually specified…
We study the classical action functional $\SMC_V$ on the free loop space of a closed, finite dimensional Riemannian manifold and the symplectic action $\AMC_V$ on the free loop space of its cotangent bundle. The critical points of both functionals can be identified with the set of perturbed closed geodesics in .…
Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as MNIST. However, these techniques are inadequate when empirically tested on comp…
Study detects endogenous bubbles in meme stocks using CI.
Precision measurements at the LHC often require analyzing high-dimensional event data for subtle kinematic signatures, which is challenging for established analysis methods. Recently, a powerful family of multivariate inference techniques that leverage both matrix element information and machine learning has been devel…
New method estimates convergence bounds for nonlinear Markov chains.
Paper detects social media influencers affecting financial markets.
Two key challenges in underlay dynamic spectrum access (DSA) are how to establish an interference limit from the primary network (PN) and how cognitive radios (CRs) in the secondary network (SN) become aware of the interference they create on the PN, especially when there is no exchange of information between the two n…
APQ jointly optimizes neural architecture, pruning, and quantization for efficient inference.