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Nomadic raises $8.4 million to wrangle the data pouring off autonomous vehicles | TechCrunch
Machine Learning

Nomadic raises $8.4 million to wrangle the data pouring off autonomous vehicles | TechCrunch

The company turns footage from robots into structured, searchable datasets with a deep learning model.

TechCrunch - AI · 6 min ·
Machine Learning

[R] VLMs Behavior for Long Video Understanding

I have extensively searched on long video understanding datasets such as Video-MME, MLVU, VideoBench, LongVideoBench and etc. What I have...

Reddit - Machine Learning · 1 min ·
UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·

All Content

[2509.25800] Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data
Nlp

[2509.25800] Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data

This paper presents a novel approach to causal discovery that accounts for latent confounders and post-treatment selection, enhancing the...

arXiv - Machine Learning · 4 min ·
[2510.01988] PepCompass: Navigating peptide embedding spaces using Riemannian Geometry
Machine Learning

[2510.01988] PepCompass: Navigating peptide embedding spaces using Riemannian Geometry

PepCompass introduces a geometry-aware framework for exploring peptide spaces, enhancing antimicrobial peptide discovery through advanced...

arXiv - Machine Learning · 4 min ·
[2508.09888] Modern Neural Networks for Small Tabular Datasets: The New Default for Field-Scale Digital Soil Mapping?
Machine Learning

[2508.09888] Modern Neural Networks for Small Tabular Datasets: The New Default for Field-Scale Digital Soil Mapping?

This article presents a comprehensive evaluation of modern neural networks for small tabular datasets in the context of digital soil mapp...

arXiv - Machine Learning · 4 min ·
[2508.04605] Multitask Learning with Stochastic Interpolants
Machine Learning

[2508.04605] Multitask Learning with Stochastic Interpolants

This article presents a new framework for multitask learning using stochastic interpolants, enhancing generative models' capabilities acr...

arXiv - Machine Learning · 3 min ·
[2507.12652] Federated Learning in Offline and Online EMG Decoding: A Privacy and Performance Perspective
Machine Learning

[2507.12652] Federated Learning in Offline and Online EMG Decoding: A Privacy and Performance Perspective

This article explores the application of federated learning (FL) in offline and online EMG decoding, addressing privacy and performance c...

arXiv - Machine Learning · 4 min ·
[2507.00031] Enhancing Spatio-Temporal Forecasting with Spatial Neighbourhood Fusion:A Case Study on COVID-19 Mobility in Peru
Machine Learning

[2507.00031] Enhancing Spatio-Temporal Forecasting with Spatial Neighbourhood Fusion:A Case Study on COVID-19 Mobility in Peru

This paper presents a novel Spatial Neighbourhood Fusion technique to enhance spatio-temporal forecasting of COVID-19 mobility in Peru, d...

arXiv - Machine Learning · 4 min ·
[2506.17344] FFINO: Factorized Fourier Improved Neural Operator for Modeling Multiphase Flow in Underground Hydrogen Storage
Machine Learning

[2506.17344] FFINO: Factorized Fourier Improved Neural Operator for Modeling Multiphase Flow in Underground Hydrogen Storage

The paper presents FFINO, a novel neural operator for modeling multiphase flow in underground hydrogen storage, demonstrating significant...

arXiv - Machine Learning · 4 min ·
[2504.07835] Pychop: Emulating Low-Precision Arithmetic in Numerical Methods and Neural Networks
Machine Learning

[2504.07835] Pychop: Emulating Low-Precision Arithmetic in Numerical Methods and Neural Networks

The paper presents Pychop, a Python library that emulates low-precision arithmetic for numerical methods and neural networks, enhancing c...

arXiv - Machine Learning · 4 min ·
[2505.23725] MuLoCo: Muon is a practical inner optimizer for DiLoCo
Llms

[2505.23725] MuLoCo: Muon is a practical inner optimizer for DiLoCo

The paper presents MuLoCo, a new inner optimizer for the DiLoCo framework, demonstrating its superior performance in training large langu...

arXiv - Machine Learning · 4 min ·
[2503.03178] Active operator learning with predictive uncertainty quantification for partial differential equations
Machine Learning

[2503.03178] Active operator learning with predictive uncertainty quantification for partial differential equations

The paper presents a lightweight predictive uncertainty quantification method for neural operators in solving partial differential equati...

arXiv - Machine Learning · 4 min ·
[2502.12981] Riemannian Variational Flow Matching for Material and Protein Design
Machine Learning

[2502.12981] Riemannian Variational Flow Matching for Material and Protein Design

The paper presents Riemannian Gaussian Variational Flow Matching (RG-VFM), a novel approach for generative modeling on curved manifolds, ...

arXiv - Machine Learning · 4 min ·
[2502.00944] Training speedups via batching for geometric learning: an analysis of static and dynamic algorithms
Machine Learning

[2502.00944] Training speedups via batching for geometric learning: an analysis of static and dynamic algorithms

This article analyzes the impact of static and dynamic batching algorithms on training speed and performance in graph neural networks (GN...

arXiv - Machine Learning · 4 min ·
[2411.09847] Towards a Fairer Non-negative Matrix Factorization
Machine Learning

[2411.09847] Towards a Fairer Non-negative Matrix Factorization

This article presents a novel approach to Non-negative Matrix Factorization (NMF) aimed at improving fairness in machine learning algorit...

arXiv - Machine Learning · 4 min ·
[2410.18424] A Causal Graph-Enhanced Gaussian Process Regression for Modeling Engine-out NOx
Machine Learning

[2410.18424] A Causal Graph-Enhanced Gaussian Process Regression for Modeling Engine-out NOx

This paper presents a novel probabilistic model using Gaussian process regression to predict engine-out NOx emissions, enhancing predicti...

arXiv - Machine Learning · 4 min ·
[2602.22122] Probing the Geometry of Diffusion Models with the String Method
Machine Learning

[2602.22122] Probing the Geometry of Diffusion Models with the String Method

This article presents a novel framework using the string method to explore the geometry of diffusion models, enhancing understanding and ...

arXiv - Machine Learning · 4 min ·
[2602.22115] Slice and Explain: Logic-Based Explanations for Neural Networks through Domain Slicing
Machine Learning

[2602.22115] Slice and Explain: Logic-Based Explanations for Neural Networks through Domain Slicing

The paper presents a novel approach called 'Slice and Explain,' which utilizes domain slicing to enhance the efficiency of logic-based ex...

arXiv - Machine Learning · 3 min ·
[2602.22086] MBD-ML: Many-body dispersion from machine learning for molecules and materials
Machine Learning

[2602.22086] MBD-ML: Many-body dispersion from machine learning for molecules and materials

The paper presents MBD-ML, a machine learning model that predicts many-body dispersion interactions in molecules and materials, enhancing...

arXiv - Machine Learning · 3 min ·
[2602.22083] Coarsening Bias from Variable Discretization in Causal Functionals
Machine Learning

[2602.22083] Coarsening Bias from Variable Discretization in Causal Functionals

This paper discusses the coarsening bias introduced by discretizing continuous variables in causal functionals, proposing a bias-reduced ...

arXiv - Machine Learning · 3 min ·
[2602.22061] Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model
Machine Learning

[2602.22061] Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model

The paper presents a novel chaotic quantum diffusion model for learning quantum data distributions, offering a more efficient and robust ...

arXiv - Machine Learning · 3 min ·
[2602.21995] Outpatient Appointment Scheduling Optimization with a Genetic Algorithm Approach
Data Science

[2602.21995] Outpatient Appointment Scheduling Optimization with a Genetic Algorithm Approach

This article presents a Genetic Algorithm framework for optimizing outpatient appointment scheduling in healthcare, demonstrating signifi...

arXiv - Machine Learning · 4 min ·
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