ML Fundamentals

Infusion: Shaping Model Behavior by Editing Training Data via Influence Functions

Discovery of Bimodal Drift Rate Structure in FRB 20240114A: Evidence for Dual Emission Regions

Weekend Project: I Built a Full MLOps Pipeline for a Credit Scoring Model (And You Can Too)

Linear Regression Is Actually a Projection Problem (Part 2: From Projections to Predictions)

Scaling seismic foundation models on AWS: Distributed training with Amazon SageMaker HyperPod and expanding context windows

Part 16: Data Manipulation in Data Validation and Quality Control

Kafka Has Become the Postgres of Streaming — And That Changes Everything

The Machine Learning Stack Is Being Rebuilt From Scratch Here's What Developers Need to Know in 2026

Perspective: Towards sustainable exploration of chemical spaces with machine learning

Epileptic Seizure Detection in Separate Frequency Bands Using Feature Analysis and Graph Convolutional Neural Network (GCN) from Electroencephalogram (EEG) Signals

Deep Networks Favor Simple Data

Improving Generalization of Deep Learning for Brain Metastases Segmentation Across Institutions

Towards Initialization-dependent and Non-vacuous Generalization Bounds for Overparameterized Shallow Neural Networks

Representation Selection via Cross-Model Agreement using Canonical Correlation Analysis

Flow-based Policy With Distributional Reinforcement Learning in Trajectory Optimization

Bridging Structured Knowledge and Data: A Unified Framework with Finance Applications

Transfer learning for nonparametric Bayesian networks

Aligning Recommendations with User Popularity Preferences

Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization

Looking into a Pixel by Nonlinear Unmixing -- A Generative Approach

AdaLoRA-QAT: Adaptive Low-Rank and Quantization-Aware Segmentation

LAtent Phase Inference from Short time sequences using SHallow REcurrent Decoders (LAPIS-SHRED)

Binned semiparametric Bayesian networks for efficient kernel density estimation

Adaptive Data-Knowledge Alignment in Genetic Perturbation Prediction

Seeing Beyond the Image: ECG and Anatomical Knowledge-Guided Myocardial Scar Segmentation from Late Gadolinium-Enhanced Images

Mousse: Rectifying the Geometry of Muon with Curvature-Aware Preconditioning

SA-CycleGAN-2.5D: Self-Attention CycleGAN with Tri-Planar Context for Multi-Site MRI Harmonization

7 Machine Learning Trends to Watch in 2026

BenchScope: How Many Independent Signals Does Your Benchmark Provide?

Rigorous Explanations for Tree Ensembles

A First Step Towards Even More Sparse Encodings of Probability Distributions

A Rational Account of Categorization Based on Information Theory

ScoringBench: A Benchmark for Evaluating Tabular Foundation Models with Proper Scoring Rules

Byzantine-Robust and Communication-Efficient Distributed Training: Compressive and Cyclic Gradient Coding

A Multi-Modal Dataset for Ground Reaction Force Estimation Using Consumer Wearable Sensors

WAter: A Workload-Adaptive Knob Tuning System based on Workload Compression

Time is Not Compute: Scaling Laws for Wall-Clock Constrained Training on Consumer GPUs

A Latent Risk-Aware Machine Learning Approach for Predicting Operational Success in Clinical Trials based on TrialsBank

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication

NeoNet: An End-to-End 3D MRI-Based Deep Learning Framework for Non-Invasive Prediction of Perineural Invasion via Generation-Driven Classification

Training deep learning based dynamic MR image reconstruction using synthetic fractals

Trimodal Deep Learning for Glioma Survival Prediction: A Feasibility Study Integrating Histopathology, Gene Expression, and MRI

Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration

Generative Data Transformation: From Mixed to Unified Data

Local Causal Discovery for Statistically Efficient Causal Inference

Provably Extracting the Features from a General Superposition

Presentation: Hidden Decisions You Don’t Know You’re Making

Kubernetes Autoscaling Demands New Observability Focus Beyond Vendor Tooling