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Machine Learning

[P] I tested Meta’s brain-response model on posts. It predicted the Elon one almost perfectly.

I built an experimental UI and visualization layer around Meta’s open brain-response model just to see whether this stuff actually works ...

Reddit - Machine Learning · 1 min ·
Machine Learning

[D] Why does it seem like open source materials on ML are incomplete? this is not enough...

Many times when I try to deeply understand a topic in machine learning — whether it's a new architecture, a quantization method, a full t...

Reddit - Machine Learning · 1 min ·
Top 10 AI certifications and courses for 2026
Ai Startups

Top 10 AI certifications and courses for 2026

This article reviews the top 10 AI certifications and courses for 2026, highlighting their significance in a rapidly evolving field and t...

AI Events · 15 min ·

All Content

Machine Learning

[D] Modeling online discourse escalation as a state machine (dataset + labeling approach)

Hi, I’ve been working on a framework to model how online discussions escalate into conflict, and I’m exploring whether it can be framed a...

Reddit - Machine Learning · 1 min ·
Machine Learning

[D] Training a classifier entirely in SQL (no iterative optimization)

I implemented SEFR, which is a lightweight linear classifier, entirely in SQL (in Google BigQuery), and benchmarked it against Logistic R...

Reddit - Machine Learning · 1 min ·
Machine Learning

[P] Awesome Jewelry AI: curated resources for AI-generated jewelry imagery (papers, datasets, open-source models, tools)

Jewelry is one of the, if not the, hardest categories for AI image generation. Reflective metals, facet edges, prong geometry, and gemsto...

Reddit - Machine Learning · 1 min ·
Machine Learning

[D] Solving the "Liquid-Solid Interface" Problem: 116 High-Fidelity Datasets of Coastal Physics (Waves, Saturated Sand, Light Transport)

Modern generative models (Sora, Runway, Kling) still struggle with the complex physics of the shoreline. I’ve spent months capturing 116 ...

Reddit - Machine Learning · 1 min ·
Open Source Ai

I am a painter with work at MoMA and the Met. I just published 50 years of my work as an open AI dataset. Here is what I learned.

I am a painter with work at MoMA and the Met. I just published 50 years of my work as an open AI dataset. Here is what I learned. I have ...

Reddit - Artificial Intelligence · 1 min ·
Open Source Ai

[D] Single-artist longitudinal fine art dataset spanning 5 decades now on Hugging Face — potential applications in style evolution, figure representation, and ethical training data

I am a figurative artist based in New York with work in the collections of the Metropolitan Museum of Art, MoMA, SFMOMA, and the British ...

Reddit - Machine Learning · 1 min ·
Ai Infrastructure

[R] Seeing arxiv endorser (eess.IV or cs.CV) CT lung nodule AI validation preprint

Sorry, I know these requests can be annoying, but I’m a medical physicist and no one I know uses arXiv. The preprint: post-deployment sen...

Reddit - Machine Learning · 1 min ·
Machine Learning

[P] Benchmark: Using XGBoost vs. DistilBERT for detecting "Month 2 Tanking" in cold email infrastructure?

I have been experimenting with Heuristic-based Deliverability Intelligence to solve the "Month 2 Tanking" problem. The Data Science Chall...

Reddit - Machine Learning · 1 min ·
Machine Learning

[P] XGBoost + TF-IDF for emotion prediction — good state accuracy but struggling with intensity (need advice)

Hey everyone, I’m working on a small ML project (~1200 samples) where I’m trying to predict: Emotional state (classification — 6 classes)...

Reddit - Machine Learning · 1 min ·
[2601.04478] Prediction of Cellular Malignancy Using Electrical Impedance Signatures and Supervised Machine Learning
Machine Learning

[2601.04478] Prediction of Cellular Malignancy Using Electrical Impedance Signatures and Supervised Machine Learning

Abstract page for arXiv paper 2601.04478: Prediction of Cellular Malignancy Using Electrical Impedance Signatures and Supervised Machine ...

arXiv - Machine Learning · 4 min ·
[2510.02282] VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL
Llms

[2510.02282] VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

Abstract page for arXiv paper 2510.02282: VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

arXiv - Machine Learning · 4 min ·
[2506.08762] EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements
Llms

[2506.08762] EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements

Abstract page for arXiv paper 2506.08762: EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements

arXiv - Machine Learning · 4 min ·
[2505.03858] Differentially Private and Scalable Estimation of the Network Principal Component
Generative Ai

[2505.03858] Differentially Private and Scalable Estimation of the Network Principal Component

Abstract page for arXiv paper 2505.03858: Differentially Private and Scalable Estimation of the Network Principal Component

arXiv - Machine Learning · 4 min ·
[2512.13872] Measuring Uncertainty Calibration
Data Science

[2512.13872] Measuring Uncertainty Calibration

Abstract page for arXiv paper 2512.13872: Measuring Uncertainty Calibration

arXiv - Machine Learning · 3 min ·
[2603.05296] Latent Policy Steering through One-Step Flow Policies
Robotics

[2603.05296] Latent Policy Steering through One-Step Flow Policies

Abstract page for arXiv paper 2603.05296: Latent Policy Steering through One-Step Flow Policies

arXiv - Machine Learning · 3 min ·
[2603.04938] Person Detection and Tracking from an Overhead Crane LiDAR
Machine Learning

[2603.04938] Person Detection and Tracking from an Overhead Crane LiDAR

Abstract page for arXiv paper 2603.04938: Person Detection and Tracking from an Overhead Crane LiDAR

arXiv - Machine Learning · 4 min ·
[2603.04859] Osmosis Distillation: Model Hijacking with the Fewest Samples
Machine Learning

[2603.04859] Osmosis Distillation: Model Hijacking with the Fewest Samples

Abstract page for arXiv paper 2603.04859: Osmosis Distillation: Model Hijacking with the Fewest Samples

arXiv - Machine Learning · 4 min ·
[2603.04425] Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification Framework for Strategic Infrastructure Management
Ai Infrastructure

[2603.04425] Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification Framework for Strategic Infrastructure Management

Abstract page for arXiv paper 2603.04425: Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification ...

arXiv - Machine Learning · 4 min ·
[2603.05327] FairFinGAN: Fairness-aware Synthetic Financial Data Generation
Machine Learning

[2603.05327] FairFinGAN: Fairness-aware Synthetic Financial Data Generation

Abstract page for arXiv paper 2603.05327: FairFinGAN: Fairness-aware Synthetic Financial Data Generation

arXiv - Machine Learning · 3 min ·
[2603.05263] A Behaviour-Aware Federated Forecasting Framework for Distributed Stand-Alone Wind Turbines
Machine Learning

[2603.05263] A Behaviour-Aware Federated Forecasting Framework for Distributed Stand-Alone Wind Turbines

Abstract page for arXiv paper 2603.05263: A Behaviour-Aware Federated Forecasting Framework for Distributed Stand-Alone Wind Turbines

arXiv - Machine Learning · 3 min ·
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Related Topics

Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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