General ML · supervised learning papers, 2023–2026
General machine learning: supervised_learning
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,425 papers are tagged with this topic.
Key findings
- General ML · supervised learning went from 263 papers in 2023 to 279 in 2026, roughly 1.1x in three years.
- NeurIPS publishes the most General ML · supervised learning work: 731 papers from 2023 to 2026, 51% of the four-venue total.
- The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 9 in 2026.
- Among the 6 topics under General Machine Learning, it ranks #3 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.1x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 98 | 45 | 44 | 76 | 263 |
| 2024 | 375 | 41 | 44 | 51 | 511 |
| 2025 | 171 | 40 | 114 | 47 | 372 |
| 2026 | 87 | 48 | 111 | 33 | 279 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
- ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
- ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
- CVPR 2026Enabling Supervised Learning of Generative Signatures for Generalized AI-Generated Images
- NeurIPS 2025$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
- ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
- ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
- CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
- NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
- ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
- ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
- CVPR 2024Efficient Hyperparameter Optimization with Adaptive Fidelity Identification
- NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
- ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
- ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
- CVPR 2023Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data
- NeurIPS 2026Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
- ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
- ICLR 2026Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling
- CVPR 2026HyperNAS Enhancing Architecture Representation for NAS Predictor via Hypernetwork
All General ML · supervised learning papers
1,424 papers, page 26 of 29
- ICLR 2023HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork
- ICLR 2023Identifiability Results for Multimodal Contrastive Learning
- ICLR 2023Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
- ICLR 2023InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
- ICLR 2023Label Propagation with Weak Supervision
- ICLR 2023Learning Controllable Adaptive Simulation for Multi-resolution Physics
- ICLR 2023Minimax Optimal Kernel Operator Learning via Multilevel Training
- ICLR 2023MocoSFL: enabling cross-client collaborative self-supervised learning
- ICLR 2023No Reason for No Supervision: Improved Generalization in Supervised Models
- ICLR 2023Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
- ICLR 2023On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.
- ICLR 2023One Transformer Can Understand Both 2D & 3D Molecular Data
- ICLR 2023Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training
- ICLR 2023Progressively Compressed Auto-Encoder for Self-supervised Representation Learning
- ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
- ICLR 2023Sampling-based inference for large linear models, with application to linearised Laplace
- ICLR 2023Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
- ICLR 2023Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance
- ICLR 2023Self-supervised learning with rotation-invariant kernels
- ICLR 2023Semi-supervised learning with a principled likelihood from a generative model of data curation
- ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
- ICLR 2023SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
- ICLR 2023Spectral Augmentation for Self-Supervised Learning on Graphs
- ICLR 2023Symmetric Pruning in Quantum Neural Networks
- ICLR 2023Temperature Schedules for self-supervised contrastive methods on long-tail data
- ICLR 2023The hidden uniform cluster prior in self-supervised learning
- ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
- ICLR 2023Transformer Meets Boundary Value Inverse Problems
- ICLR 2023Unbiased Supervised Contrastive Learning
- ICLR 2023Understanding The Robustness of Self-supervised Learning Through Topic Modeling
- ICLR 2023Weighted Ensemble Self-Supervised Learning
- ICLR 2023What shapes the loss landscape of self supervised learning?
- ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
- ICML 2023A Neural PDE Solver with Temporal Stencil Modeling
- ICML 2023Active Ranking of Experts Based on their Performances in Many Tasks
- ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
- ICML 2023AutoCoreset: An Automatic Practical Coreset Construction Framework
- ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
- ICML 2023Continual Learners are Incremental Model Generalizers
- ICML 2023CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations
- ICML 2023Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
- ICML 2023Dimensionality Reduction for General KDE Mode Finding
- ICML 2023Disentangled Multi-Fidelity Deep Bayesian Active Learning
- ICML 2023Distance Weighted Supervised Learning for Offline Interaction Data
- ICML 2023Evaluating Self-Supervised Learning via Risk Decomposition
- ICML 2023Fast Sampling of Diffusion Models via Operator Learning
- ICML 2023Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods
- ICML 2023GNOT: A General Neural Operator Transformer for Operator Learning
- ICML 2023Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression
- ICML 2023Learning Neural PDE Solvers with Parameter-Guided Channel Attention
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FAQ
- How many General ML · supervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 1,425 in total: 263 in 2023, 511 in 2024, 372 in 2025, 279 in 2026.
- How many General ML · supervised learning papers are at NeurIPS 2026?
- NeurIPS 2026 has 87 General ML · supervised learning papers, versus 171 the year before.
- How many General ML · supervised learning papers are at ICLR 2026?
- ICLR 2026 has 48 General ML · supervised learning papers, versus 40 the year before.
- How many General ML · supervised learning papers are at ICML 2026?
- ICML 2026 has 111 General ML · supervised learning papers, versus 114 the year before.
- How many General ML · supervised learning papers are at CVPR 2026?
- CVPR 2026 has 33 General ML · supervised learning papers, versus 47 the year before.
- Which conference publishes the most General ML · supervised learning papers?
- NeurIPS, with 731 papers from 2023 to 2026.