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 “prior-alignment”

Preconditioned One-Step Generative Modeling for Bayesian Inverse Problems in Function Spacesstat.ML

A new machine learning method for Bayesian inverse problems in function spaces.

problem Bayesian inverse problems in function spaces with incompatibility of white noise sources.

method One-step generative transport with amortized neural operator and prior-aligned Gaussian random field.

result Generative operator trained on prior samples and noisy observations generates posterior samples efficiently.

Bayesian inverse problems function spaces one-step transport amortized neural operator prior-aligned GRF

2026-03-16abs ↗pdf ↗

Prior-Aligned Meta-RL: Thompson Sampling with Learned Priors and Guarantees in Finite-Horizon MDPscs.LG

New meta-reinforcement learning method improves performance in finite-horizon MDPs.

problem Improving meta-reinforcement learning in finite-horizon MDPs with shared optimal action-value functions.

method Proposes MTSRL and MTSRL+ algorithms with learned priors and covariance, coupled with prior-alignment technique for meta-regret guarantees.

result Achieves meta-regret guarantees with learned priors and covariance, outperforming prior-independent RL and bandit-only meta-baselines.

meta-reinforcement learning finite-horizon MDPs Thompson sampling prior-alignment meta-regret guarantees

2025-10-06abs ↗pdf ↗

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriorscs.LG

This work explores how overparametrization and priors affect Bayesian neural network posteriors.

problem Symmetries, non-identifiabilities, and weight-space priors fragment and inflate BNN posteriors.

method We study the interplay between overparametrization and priors in BNN posteriors, deriving key phenomena and validating through experiments.

result Overparametrization induces structured, prior-aligned weight posterior distributions.

Bayesian neural networks posteriors overparametrization priors symmetries

2026-03-23abs ↗pdf ↗

Meta Dynamic Pricing: Transfer Learning Across Experimentscs.LG

We study the problem of learning shared structure \emph{across} a sequence of dynamic pricing experiments for related products. We consider a practical formulation where the unknown demand parameters for each product come from an unknown distribution (prior) that is shared across products. We then propose a meta dynami…

2019-02-28abs ↗pdf ↗

Robust Causal Discovery under Imperfect Structural Constraintscs.LG

New method robustly discovers causal relationships from imperfect data.

problem Challenges in causal discovery from imperfect structural constraints.

method Prior alignment and conflict resolution through surrogate model and multi-task learning.

result Proposes a robust method for causal discovery under imperfect constraints.

causal discovery imperfect constraints robustness multi-task learning surrogate model

2025-11-10abs ↗pdf ↗

Constructing VAE Latent Spaces with Prescribed Topologycs.LG

Constructing VAE Latent Spaces with Prescribed Topology

problem Resolving topological mismatch in VAEs for non-Euclidean data

method A constructive framework for product covering spaces

result Topology-aware latent representations with closed-form KL divergences

VAE topology product covering space KL divergence topological mismatch

2026-06-05abs ↗pdf ↗

BaGGLS: A Bayesian Shrinkage Framework for Interpretable Modeling of Interactions in High-Dimensional Biological Datastat.ME

BaGGLS models biological interactions using Bayesian shrinkage for interpretability.

problem Interpreting complex interactions in high-dimensional biological data.

method Bayesian group global-local shrinkage prior with variational approximation.

result BaGGLS outperforms other methods in interaction detection and scalability.

Bayesian shrinkage interactions high-dimensional data interpretability genomics

2025-11-19abs ↗pdf ↗