Data analysis, statistics, and data engineering
Tl,dr : suggest me a solution to create a ai ml project where user will give his dataset as input and the project should give best model ...
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Hi all, I’m curious about the current review dynamics for ICML 2026, especially after the rebuttal phase. For those who are reviewers (or...
![[2508.14734] AFABench: A Generic Framework for Benchmarking Active Feature Acquisition](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
AFABench introduces a benchmark framework for Active Feature Acquisition (AFA), addressing the need for standardized evaluation of AFA me...
This article evaluates 25 pretrained molecular embedding models for molecular representation learning, revealing that most show little im...
This article presents a novel approach to predicting the virality of memes on Reddit using a multimodal dataset and advanced machine lear...
The paper presents GEDAN, a novel Graph Neural Network framework that learns edit costs for Graph Edit Distance (GED), addressing limitat...
The paper presents JEF-Hinter, a system designed to enhance the adaptation of web agents by leveraging offline knowledge, improving perfo...
The paper presents Modular Delta Merging with Orthogonal Constraints (MDM-OC), a framework for scalable and reversible model composition ...
This paper introduces a novel framework for Graph Neural Networks (GNNs) that utilizes a one-hot graph encoder embedding (GEE) to enhance...
This article presents a novel framework, BioEmu-CV, for automatically learning collective variables (CVs) from molecular dynamics simulat...
GenesisGeo presents a novel approach to geometric reasoning by introducing a large-scale dataset and a multi-task training paradigm that ...
This article presents Symbolic Branch Networks (SBNs), a novel neural model that integrates decision tree structures for enhanced interpr...
This paper explores a novel approach to solving Markov decision problems (MDPs) using approximate linear programming with a log barrier f...
The paper introduces MoNE, a novel method for structured pruning of Mixture-of-Experts (MoE) models, replacing redundant experts with lig...
This study presents an AI-based framework to analyze tourist perceptions in historic urban quarters of Shanghai, utilizing multimodal soc...
This article explores the use of large language models (LLMs) to identify new research directions in materials science by analyzing scien...
This article presents a novel method, Physics-Based Flow Matching (PBFM), which integrates physical constraints into generative modeling,...
The paper presents MOFh6, a large language model system that enhances the extraction of synthesis conditions for metal-organic frameworks...
The paper presents SuperMAN, a framework designed for learning from temporally sparse and heterogeneous data, enhancing interpretability ...
This paper presents a novel geometric perspective on diffusion models, revealing flaws in traditional decoding methods and proposing a ne...
The paper introduces Covariance Density Neural Networks (CDNN), enhancing graph neural networks by using the sample covariance matrix as ...
FairSHAP introduces a novel preprocessing framework that utilizes Shapley value attribution to enhance fairness in machine learning model...
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