On-device research index

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.

168,657 papers · 148 categories

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7 results for “distribution-sensitive”

Distributionally Robust Causal Inference with Observational Datastat.ME

New framework for estimating treatment effects in observational studies.

problem Estimating average treatment effects in the presence of unobserved confounders.

method Distributionally robust optimization, sensitivity models.

result Sharp bounds on average treatment effects under distributional assumptions.

causal inference observational studies distributionally robust optimization sensitivity models unobserved confounders

2022-10-15abs ↗pdf ↗

Homophily Outlier Detection in Non-IID Categorical Datacs.LG

New framework detects outliers in non-IID categorical data.

problem Existing outlier detection methods fail in non-IID data.

method Value-value graph-based representation and outlierness propagation.

result Significant improvement in AUC on complex data sets.

outlier detection non-IID data categorical data distribution-sensitive

2021-03-21abs ↗pdf ↗

ForestDSH: A Universal Hash Design for Discrete Probability Distributionscs.LG

In this paper, we consider the problem of classification of $M$ high dimensional queries $y^1,\cdots,y^M\in B^S$ to $N$ high dimensional classes $x^1,\cdots,x^N\in A^S$ where $A$ and $B$ are discrete alphabets and the probabilistic model that relates data to the classes $P(x,y)$ is known. This problem has applications …

2019-05-11abs ↗pdf ↗

A Bayesian analysis of gain-loss asymmetryq-fin.ST

Bayesian analysis reveals asymmetry in financial data.

problem Quantifying asymmetry in financial time series data.

method Bayesian approach, t-Test generalization, two data distribution models, sensitivity analysis.

result Statistical significance of gain/loss asymmetry amounts.

Bayesian analysis financial time series gain/loss asymmetry t-Test data distribution

2021-04-13abs ↗pdf ↗

Neural Conditional Transport Mapscs.LG

Neural framework for conditional OT maps learns from categorical and continuous variables.

problem Learning conditional optimal transport maps between complex distributions.

method Hypernetwork generates adaptive transport layer parameters based on conditioning variables.

result Our method outperforms simpler conditioning methods in comprehensive ablation studies.

conditional optimal transport neural networks probability distributions sensitivity analysis

2025-05-21abs ↗pdf ↗

Data-driven topology design using a deep generative modelphysics.comp-ph

Paper proposes a new method for designing materials using deep learning.

problem Designing high-performance material distributions from given distributions.

method Iterative process of selecting, generating, and merging material distributions using a deep generative model.

result The method improves material performance through iterative refinement.

topology design deep learning material distribution sensitivity-free multi-objective

2020-06-08abs ↗pdf ↗

Distributional Sensitivity Analysis: Enabling Differentiability in Sample-Based Inferencestat.ML

Two formulae estimate sensitivity of random vectors to distributional parameters.

problem Estimating sensitivity of random vectors to distributional parameters.

method Two analytical formulae and four numerical algorithms.

result Validated numerical algorithms and demonstrated effectiveness.

sensitivity analysis differentiability random vectors distributional parameters inverse problems

2025-08-12abs ↗pdf ↗