General ML · supervised learning papers, 2023–2026

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.

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

41 papers, page 1 of 1

1. ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
2. ICLR 2024AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
3. ICLR 2024Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
4. ICLR 2024Efficient Integrators for Diffusion Generative Models
5. ICLR 2024Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
6. ICLR 2024Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials
7. ICLR 2024Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
8. ICLR 2024Fair Classifiers that Abstain without Harm
9. ICLR 2024Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
10. ICLR 2024From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
11. ICLR 2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
12. ICLR 2024Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
13. ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
14. ICLR 2024LDReg: Local Dimensionality Regularized Self-Supervised Learning
15. ICLR 2024Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
16. ICLR 2024Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
17. ICLR 2024Masked Distillation Advances Self-Supervised Transformer Architecture Search
18. ICLR 2024Memorization in Self-Supervised Learning Improves Downstream Generalization
19. ICLR 2024MgNO: Efficient Parameterization of Linear Operators via Multigrid
20. ICLR 2024Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
21. ICLR 2024Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
22. ICLR 2024Modulate Your Spectrum in Self-Supervised Learning
23. ICLR 2024Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.
24. ICLR 2024Neural Auto-designer for Enhanced Quantum Kernels
25. ICLR 2024Neural Fourier Transform: A General Approach to Equivariant Representation Learning
26. ICLR 2024Neural Spectral Methods: Self-supervised learning in the spectral domain
27. ICLR 2024P2Seg: Pointly-supervised Segmentation via Mutual Distillation
28. ICLR 2024PubDef: Defending Against Transfer Attacks From Public Models
29. ICLR 2024Rethinking the Uniformity Metric in Self-Supervised Learning
30. ICLR 2024Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
31. ICLR 2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
32. ICLR 2024Self-supervised Representation Learning from Random Data Projectors
33. ICLR 2024SemiReward: A General Reward Model for Semi-supervised Learning
34. ICLR 2024Spectrally Transformed Kernel Regression
35. ICLR 2024Supervised Knowledge Makes Large Language Models Better In-context Learners
36. ICLR 2024The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
37. ICLR 2024Towards a statistical theory of data selection under weak supervision
38. ICLR 2024Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
39. ICLR 2024Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
40. ICLR 2024Vanishing Gradients in Reinforcement Finetuning of Language Models
41. ICLR 2024Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data

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.