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arXiv research

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.

168,742 papers · 148 categories

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6 results for “noise-resistance”

A Noise-robust Multi-head Attention Mechanism for Formation Resistivity Prediction: Frequency Aware LSTMcs.LG

FAL improves formation resistivity prediction from cased boreholes with noise resistance.

problem Noise and high-frequency disaster in predicting formation resistivity from cased boreholes.

method Frequency-aware framework and temporal anti-noise block for LSTM.

result FAL achieves a 24.3% improvement in R2 over LSTM, reaching R2=0.91.

formation resistivity cased borehole transient electromagnetic noise resistance multi-head attention

2024-06-06abs ↗pdf ↗

A Stable Distance Persistence Homology for Dynamic Bayesian Network Clusteringmath.AT

Stable topological summary captures evolving dependency structure in dynamic Bayesian networks.

problem Missing larger-scale patterns in evolving dependency structures in dynamic Bayesian networks.

method Topological approach using Dynamic Bayesian Graphs and persistent homology.

result Stable topological summary (barcodes) captures evolving dependency structure in DBNs.

dynamic bayesian networks topological data analysis persistent homology dependency structure noise-resistance

2026-05-11abs ↗pdf ↗

Polygon Recognition and Symmetry Detectionmath.DG

We introduce an approach based on moving frames for polygon recognition and symmetry detection. We present detailed algorithms for recognition of polygons modulo the special Euclidean, Euclidean, equi-affine, skewed-affine and similarity Lie groups, and explain the procedure for a generic Lie group. The time complexity…

2000-11-17abs ↗pdf ↗

Cluster Forestsstat.ME

With inspiration from Random Forests (RF) in the context of classification, a new clustering ensemble method---Cluster Forests (CF) is proposed. Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral clustering to obtain cluster assignments fo…

2011-04-14abs ↗pdf ↗

Reliable data clustering with Bayesian community detectionstat.ML

Bayesian methods detect clusters in noisy data more reliably.

problem Noisy data distorts traditional clustering methods, leading to unreliable results.

method Bayesian community detection using Minimum Description Length principle.

result Bayesian methods identify more robust clusters in noisy data.

Bayesian community detection Minimum Description Length Stochastic Block Model Regularized Map Equation gene co-expression

2025-10-16abs ↗pdf ↗

Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settingsstat.ML

Bayesian deep learning improves out-of-distribution detection but not always.

problem Improving the reliability of deep learning models in uncertain or novel data.

method Validation of likelihood-based Bayesian models for out-of-distribution detection.

result Bayesian deep learning models can marginally outperform conventional neural networks in certain conditions.

Bayesian deep learning out-of-distribution detection likelihood models neural networks curse of dimensionality

2020-09-03abs ↗pdf ↗