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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.

169,051 papers · 148 categories

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1122 · Sep 201819922001200920182026
16 results for F0.5

PHBench predicts Series A funding from Product Hunt launch signals with 7.8% accuracy.

problem Predicting startup Series A funding from launch signals on Product Hunt.
method Constructed PHBench from 67,292 Product Hunt posts, linked to funding records, and used a three-component ensemble model.
result Best-performing model achieved F0.5 = 0.097 and AP = 0.037, with a statistically significant advantage over logistic regression.

We provide a combinatorial presentation of the set F of 3-dimensional generic flows, namely the set of pairs (M,v) with M a compact oriented 3-manifold and v a nowhere-zero vector field on M having generic behaviour along the boundary of M, with M viewed up to diffeomorphism and v up to homotopy on M fixed on the bound…

2012-11-27abs ↗pdf ↗

Real music signals are highly variable, yet they have strong statistical structure. Prior information about the underlying physical mechanisms by which sounds are generated and rules by which complex sound structure is constructed (notes, chords, a complete musical score), can be naturally unified using Bayesian modell…

2016-06-03abs ↗pdf ↗

Unsupervised model generates distinct intonation codes for speech synthesis.

problem Lack of understanding of what prosodic variations are controlled in speech synthesis.
method Phrase-level variational autoencoder with multi-modal prior, using mode centres as intonation codes.
result Generated intonation codes are perceptually distinct and carry various affect-related styles.

WaveCycleGAN converts synthetic speech to natural speech using cycle-consistent adversarial networks.

problem Over-smoothing effect in synthetic speech, leading to quality degradation.
method Cycle-consistent adversarial networks for waveform-level modification.
result Improves naturalness of generated speech sounds.

DeepTrust uses NLP to quickly identify and verify financial anomalies on Twitter.

problem Unreliable information in financial markets leading to unexpected price changes.
method Machine learning for anomaly detection, NLP for information retrieval and reliability assessment.
result DeepTrust outperforms baseline classifiers in identifying financial anomalies.