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.

168,742 papers · 148 categories

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7 results for “Simulator-assisted”

Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Controlcs.LG

A green simulation-assisted reinforcement learning method for biomanufacturing.

problem Complexity, high variability, lead time, and limited historical data in biopharmaceutical manufacturing.

method Quantifies model risk, uses posterior distribution, and selectively reuses simulation data.

result Demonstrates promising performance in online learning and decision making.

reinforcement learning biomanufacturing model risk green simulation process learning

2020-06-17abs ↗pdf ↗

SimVAE: Simulator-Assisted Training forInterpretable Generative Modelsstat.ML

SimVAE trains interpretable VAEs using simulators.

problem Training interpretable generative models.

method Two-step process: train decoder to approximate simulator, then train encoder to invert it.

result Disentangled and interpretable latent space achieved.

Simulator-assisted Variational autoencoder Interpretable latent space Deep learning Generative models

2019-11-19abs ↗pdf ↗

Simulation Assisted Likelihood-free Anomaly Detectionhep-ph

New method combines simulations and data for anomaly detection.

problem Detecting new particle signals without direct evidence.

method Hybrid approach using reweighting and interpolation.

result Improved background estimation and classification.

anomaly detection likelihood-free simulation-assisted jet substructure supervised learning

2020-01-14abs ↗pdf ↗

Simulation-Assisted Decorrelation for Resonant Anomaly Detectionhep-ph

Two methods use simulation to improve anomaly detection in particle physics.

problem Artificial bumps in invariant mass spectra from machine learning classifiers.

method Simulation-assisted decorrelation techniques.

result Both methods are robust to correlations in the data and improve anomaly detection.

anomaly detection resonant physics machine learning decorrelation simulation

2020-09-04abs ↗pdf ↗

Resonant Anomaly Detection with Multiple Reference Datasetshep-ph

Enhances anomaly detection using multiple reference datasets.

problem Lack of performance with multiple reference datasets.

method Generalizes existing techniques CWoLa and SALAD for multiple reference datasets.

result Improved performance across various settings.

anomaly detection multiple datasets weak supervision finite-sample guarantees

2022-12-20abs ↗pdf ↗

Simulation assisted machine learningstat.ML

Motivation: In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making predictions. When sufficient system details are not known, one typically turns to machine learning, which builds a black-box model of the system using a large dataset of in…

2018-02-15abs ↗pdf ↗

Convex Latent Effect Logit Model via Sparse and Low-rank Decompositioncs.LG

Proposes a convex model for mixed logit to handle individual heterogeneity.

problem Non-convex optimization in mixed logit models for individual heterogeneity.

method Sparse and low-rank decomposition for convex formulation.

result Convex formulation avoids simulation-based approximation and unstable model interpretation.

logistic regression mixed logit heterogeneity convex optimization sparse decomposition

2021-08-22abs ↗pdf ↗