Statistics - Machine Learning

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Machine Learning Enhancing DeepONet with Random Sampling Techniques

New training method improves efficiency and accuracy of DeepONet for complex predictions.

Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami

2025-06-01T21:22:40+00:00 ― 6 min read

Statistical Finance Analyzing Stock Price Predictions with Deep Learning

Study reveals insights on stock price predictions using deep learning techniques.

Kyungsub Lee

2025-06-01T17:12:20+00:00 ― 5 min read

Solar and Stellar Astrophysics Advances in Predicting Solar Flares

A new method improves predictions of solar flares, enhancing safety for astronauts and technology.

MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

2025-06-01T13:52:04+00:00 ― 6 min read

Machine Learning Advancements in Causal Model Testing

New methods enhance efficiency in testing causal models with hidden variables.

Hyunchai Jeong, Adiba Ejaz, Jin Tian

2025-06-01T12:11:56+00:00 ― 7 min read

Machine Learning The Need for Better Explainable AI Methods

Current explainable AI methods fall short in clarity and reliability.

Stefan Haufe, Rick Wilming, Benedict Clark

2025-06-01T11:21:52+00:00 ― 6 min read

Numerical Analysis Bayesian Filtering: A Tool for State Estimation

Learn how Bayesian filtering tackles noisy observations to estimate system states.

Kasper Bågmark, Adam Andersson, Stig Larsson

2025-06-01T10:31:48+00:00 ― 5 min read

Machine Learning New Method Tackles Membership Inference Attacks in LLMs

Researchers present a cost-effective approach to privacy risks in large language models.

Rongting Zhang, Martin Bertran, Aaron Roth

2025-06-01T09:41:44+00:00 ― 6 min read

Quantum Physics Quantum Machine Learning in Drug Discovery

Quantum machine learning merges quantum computing and drug discovery for efficient solutions.

Anthony M. Smaldone, Yu Shee, Gregory W. Kyro

2025-06-01T08:01:36+00:00 ― 6 min read

Econometrics Analyzing Price Elasticity in Electricity Demand

A look at how price influences electricity demand using advanced estimation techniques.

Silvana Tiedemann, Jorge Sanchez Canales, Felix Schur

2025-06-01T04:41:20+00:00 ― 6 min read

Machine Learning Addressing Distribution Shift in Machine Learning Models

A look at the challenges of distribution shift and its impact on predictions.

Alex Nguyen, David J. Schwab, Vudtiwat Ngampruetikorn

2025-06-01T03:51:16+00:00 ― 6 min read

Machine Learning Advancements in Uncertainty Quantification in Data Analysis

Explore adaptive conformal inference and confidence predictors for reliable data predictions.

Johan Hallberg Szabadváry

2025-06-01T03:01:12+00:00 ― 5 min read

Machine Learning Harmonic Path Integral Diffusion: A New Sampling Method

Introducing H-PID, a method for efficient sampling from complex data distributions.

Hamidreza Behjoo, Michael Chertkov

2025-06-01T00:31:00+00:00 ― 4 min read

Machine Learning Adapting Machine Learning Training for Bigger Models

Explores new methods for training larger machine learning models effectively.

Lechao Xiao

2025-05-31T23:40:56+00:00 ― 6 min read

Machine Learning Simplifying Contextual Bandits for Operators

A user-friendly tool for understanding contextual bandit systems.

Andrew Maher, Matia Gobbo, Lancelot Lachartre

2025-05-31T22:50:52+00:00 ― 6 min read

Machine Learning Advancing Data Modeling with DrMMD Technique

A look into DrMMD and its application for better data distribution modeling.

Zonghao Chen, Aratrika Mustafi, Pierre Glaser

2025-05-31T22:00:48+00:00 ― 5 min read

Machine Learning Advancements in Time-Series Forecasting Techniques

Learn how adaptive conformal inference improves multi-step predictions in forecasting.

Johan Hallberg Szabadváry

2025-05-31T21:10:44+00:00 ― 5 min read

Machine Learning Learning Dynamics from Partial Observations in Complex Systems

Research on estimating dynamics from noisy and bilinear measurements.

Yahya Sattar, Yassir Jedra, Sarah Dean

2025-05-31T11:02:58+00:00 ― 6 min read

Machine Learning Estimating Causal Effects: Weights and Representations

A deep dive into causal effects estimation through weights and learned representations.

Oscar Clivio, Avi Feller, Chris Holmes

2025-05-31T09:40:20+00:00 ― 9 min read

Machine Learning Evaluating Generative Models: A Non-Parametric Approach

A new method for assessing generative models using non-parametric tests.

Samuele Grossi, Marco Letizia, Riccardo Torre

2025-05-31T08:17:42+00:00 ― 8 min read

Machine Learning Collaborative Learning Framework: A New Approach

A method for agents to improve estimates through teamwork and feedback.

Getachew K Befekadu

2025-05-31T06:55:04+00:00 ― 5 min read

Applications A New Approach to Economic Changes in LMICs

Innovative methods to analyze economic shifts despite data challenges.

Ronald Katende

2025-05-31T00:01:54+00:00 ― 7 min read

Optimization and Control The Extragradient Method: A Key to Complex Problem Solving

Discover the extragradient method and its role in solving optimization problems.

Quoc Tran-Dinh, Nghia Nguyen-Trung

2025-05-30T22:39:16+00:00 ― 5 min read

Machine Learning Improving Conditional Coverage in Predictive Models

New method enhances prediction reliability for diverse groups in high-stakes scenarios.

Ruijiang Gao, Mingzhang Yin, James McInerney

2025-05-30T19:54:00+00:00 ― 5 min read

Methodology Predicting Rice Yields in Peru Using Modern Techniques

This study examines data-driven methods to forecast rice production in Peru.

Rita Rocio Guzman-Lopez, Luis Huamanchumo, Kevin Fernandez

2025-05-30T17:08:44+00:00 ― 5 min read

Machine Learning Conditional Generative Models: Shaping Data with Precision

Explore how conditional generative models create tailored data for various applications.

Hanwen Huang

2025-05-30T15:46:06+00:00 ― 5 min read

Computer Vision and Pattern Recognition Improving Depth Estimation with PEFT Methods

Exploring parameter-efficient fine-tuning for depth estimation accuracy and uncertainty.

Richard D. Paul, Alessio Quercia, Vincent Fortuin

2025-05-30T14:23:28+00:00 ― 4 min read

Machine Learning Enhancing Physics-Informed Neural Networks with DCGD

A new method to improve training in physics-informed neural networks.

Youngsik Hwang, Dong-Young Lim

2025-05-30T06:07:40+00:00 ― 6 min read

Machine Learning Efficient Parameter Estimation with Embed and Emulate

A new approach for faster parameter estimation in complex systems using simulations.

Ruoxi Jiang, Peter Y. Lu, Rebecca Willett

2025-05-30T04:45:02+00:00 ― 6 min read

Machine Learning Addressing Confirmation Bias in Semi-Supervised Learning

A framework to balance pseudo-label learning in machine learning.

Yu Wang, Yuxuan Yin, Peng Li

2025-05-30T03:22:24+00:00 ― 5 min read

Machine Learning Improving Forecast Stability in Supply Chains

A method to enhance stability in forecasts while maintaining accuracy in business planning.

Daan Caljon, Jeff Vercauteren, Simon De Vos

2025-05-30T01:59:46+00:00 ― 6 min read

Machine Learning Learning from Unnormalized Distributions: Overview and Techniques

This article discusses methods for learning unnormalized distributions using noise-contrastive estimation.

J. Jon Ryu, Abhin Shah, Gregory W. Wornell

2025-05-30T00:37:08+00:00 ― 5 min read

Machine Learning New Framework to Improve Machine Learning Adaptability

A graph-based approach to enhance machine learning in dynamic environments.

Han Wang, Yixuan Li

2025-05-29T23:14:30+00:00 ― 6 min read

Machine Learning Advancements in Event Prediction Frameworks

A new model improves efficiency in predicting events over time.

Aristeidis Panos

2025-05-29T21:51:52+00:00 ― 8 min read

Quantitative Methods Understanding Shapley Values in DNA Profiling

Shapley values enhance decision-making in DNA profiling and related fields.

Lauren Elborough, Duncan Taylor, Melissa Humphries

2025-05-29T20:29:14+00:00 ― 6 min read

Machine Learning Neural Networks in High-Dimensional Data

Exploring how neural networks tackle high-dimensional challenges in classification tasks.

Andres Felipe Lerma-Pineda, Philipp Petersen, Simon Frieder

2025-05-29T19:06:36+00:00 ― 5 min read

Machine Learning Enhancing Neural Performance Through Feature Learning

Research highlights how feature learning improves neural network performance effectively.

Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

2025-05-29T17:43:58+00:00 ― 7 min read

Machine Learning Improving Classification with Enriched Functional Tree-Based Classifiers

A new method enhances classification of high-dimensional time-series data using functional analysis.

Fabrizio Maturo, Annamaria Porreca

2025-05-29T16:21:20+00:00 ― 7 min read

Machine Learning Advancements in Transfer Learning Techniques

Exploring effective strategies for hyperparameter selection in transfer learning.

Koki Okajima, Tomoyuki Obuchi

2025-05-29T14:58:42+00:00 ― 5 min read

Machine Learning Balancing Fairness and Performance in Machine Learning

A new method offers a simpler way to compute fairness-performance balance in machine learning.

Mark Kozdoba, Binyamin Perets, Shie Mannor

2025-05-29T13:36:04+00:00 ― 6 min read

Machine Learning A Bayesian Approach to Change Point Detection in Hawkes Processes

This article presents a new method for identifying changes in event data.

Zeyue Zhang, Xiaoling Lu, Feng Zhou

2025-05-29T12:13:26+00:00 ― 5 min read