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.

169,341 papers · 148 categories

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11 results for “network-guided”

Network-Guided Biomarker Discoverystat.ML

New methods use network data to find genetic indicators for diseases.

problem Finding genetic indicators for diseases from large, complex data.

method Integrating network data to select features from whole-genome data.

result Methods can identify genetic indicators that work together.

precision medicine feature selection genetic indicators network-guided biomarker discovery

2016-07-27abs ↗pdf ↗

Knowledge-augmented Column Networks: Guiding Deep Learning with Advicecs.LG

Proposes a deep learning framework guided by human advice.

problem Learning from sparse and noisy data.

method Knowledge-augmented Column Networks, leveraging human advice.

result Improves model performance in domains with structured representations.

deep learning human guidance sparse data systematic noise knowledge augmentation

2019-05-31abs ↗pdf ↗

Recursive KalmanNet: Analyse des capacités de généralisation d'un réseau de neurones récurrent guidé par un filtre de Kalmaneess.SP

Recursive KalmanNet generalizes well in noisy, out-of-distribution scenarios.

problem Generalization in noisy, out-of-distribution scenarios.

method Recurrent neural network guided by a Kalman filter.

result Recursive KalmanNet performs well in scenarios with different temporal dynamics from training data.

Kalman filter Recurrent neural network Generalization Noisy data Out-of-distribution

2025-06-25abs ↗pdf ↗

Learning on heterogeneous graphs using high-order relationsstat.ML

New method for learning on heterogeneous graphs without meta-paths.

problem Learning on heterogeneous graphs is sensitive to meta-paths choice, leading to poor performance.

method Decompose heterogeneous graph into homogeneous relation-type graphs, combine higher-order representations, use attention mechanisms.

result Our model outperforms state-of-the-art baselines in vertex classification tasks on heterogeneous graph datasets.

heterogeneous graphs higher-order relations attention mechanisms vertex classification meta-paths

2021-03-29abs ↗pdf ↗

Graph Neural Network Guided Local Search for the Traveling Salesperson Problemcs.LG

Graph Neural Networks and Guided Local Search improve TSP solutions.

problem Finding optimal solutions to the Traveling Salesperson Problem quickly.

method Hybrid approach combining Graph Neural Networks and Guided Local Search.

result Significant reduction in optimality gap for TSP solutions.

Traveling Salesperson Problem Graph Neural Networks Local Search Optimization Transportation

2021-10-11abs ↗pdf ↗

Efficient network-guided multi-locus association mapping with graph cutsstat.ML

As an increasing number of genome-wide association studies reveal the limitations of attempting to explain phenotypic heritability by single genetic loci, there is growing interest for associating complex phenotypes with sets of genetic loci. While several methods for multi-locus mapping have been proposed, it is often…

2012-11-10abs ↗pdf ↗

Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Networkeess.SP

Efficiently quantifies uncertainty in subsurface flow using neural networks guided by theory.

problem Uncertainty in dynamic subsurface flow predictions.

method Theory-guided Neural Network (TgNN) for efficient uncertainty quantification.

result TgNN surrogate improves efficiency of uncertainty quantification compared to MC method.

subsurface flow uncertainty quantification neural networks stochastic parameters Monte Carlo

2020-04-25abs ↗pdf ↗

Fast Bayesian Inference for Neutrino Non-Standard Interactions at Dark Matter Direct Detection Experimentscs.LG

We accelerate Bayesian inference for neutrino physics experiments by 100-60x.

problem Complex posterior geometries in multi-dimensional parameter spaces.

method GPU acceleration, automatic differentiation, neural-network-guided reparameterization.

result Significant performance improvements in Bayesian inference for direct detection experiments.

neutrino physics Bayesian inference neural networks GPU acceleration dark matter

2024-05-23abs ↗pdf ↗

Dense Hebbian neural networks: a replica symmetric picture of supervised learningcond-mat.dis-nn

Dense neural networks learn efficiently with large datasets and noise.

problem Training neural networks with large, noisy datasets.

method Statistical mechanics and Monte Carlo simulations.

result Dense neural networks can handle large amounts of patterns and recognize patterns at high signal-to-noise ratios.

neural networks supervised learning statistical mechanics Monte Carlo large datasets

2022-11-25abs ↗pdf ↗

Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learningcs.AI

Proposes efficient algorithm for system-level I&M decisions under uncertainty.

problem Optimal management strategies for deteriorating civil engineering systems.

method Factored partially observable Markov decision process with Bayesian networks and DDMAC reinforcement learning.

result DDMAC policies offer substantial benefits over heuristic approaches in system-level cost optimization.

Bayesian networks reinforcement learning deteriorating systems civil engineering deep learning

2022-09-02abs ↗pdf ↗

Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labelscs.LG

Accelerates DNN robustness verification with target labels.

problem Improving the robustness of deep neural networks against adversarial attacks.

method Guiding robustness verification with target labels, reducing search space and using symbolic interval propagation and linear relaxation.

result Significantly improves DNN verification speed by 36X, especially when perturbation distance is reasonable.

Deep Neural Networks Robustness Verification Adversarial Attacks Symbolic Interval Propagation Linear Relaxation

2020-07-16abs ↗pdf ↗