Deep learning · representation learning papers, 2023–2026

Key findings

• Deep learning · representation learning fell from 259 papers in 2023 to 214 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · representation learning work: 279 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 11 in 2023 to 28 in 2026.
• Among the 11 topics under Deep Learning, it ranks #7 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.8x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
• ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
• ICLR 2026Boosting Open Set Recognition Performance through Modulated Representation Learning
• CVPR 2026CanonCGT Reference-Based Color Grading via Canonical Pivot Representation
• NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
• ICML 2025Banyan: Improved Representation Learning with Explicit Structure
• ICLR 2025Edge-aware Image Smoothing with Relative Wavelet Domain Representation
• CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
• NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
• ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
• ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
• CVPR 2024Disentangled Prompt Representation for Domain Generalization
• NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
• ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
• ICLR 2023Bispectral Neural Networks
• CVPR 2023AnyFlow: Arbitrary Scale Optical Flow With Implicit Neural Representation
• NeurIPS 2026Approximation in Contrastive Representation Learning
• ICML 2026Amortized Maximum Inner Product Search with Learned Support Functions
• ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
• CVPR 2026Enhancing Visual Representation with Textual Semantics Textual Semantics-Powered Prototypes for

All Deep learning · representation learning papers

42 papers, page 1 of 1

1. ICML 2024A Distributional Analogue to the Successor Representation
2. ICML 2024A Sparsity Principle for Partially Observable Causal Representation Learning
3. ICML 2024Autoencoding Conditional Neural Processes for Representation Learning
4. ICML 2024Causal Representation Learning from Multiple Distributions: A General Setting
5. ICML 2024Causal Representation Learning Made Identifiable by Grouping of Observational Variables
6. ICML 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
7. ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
8. ICML 2024Deep Regression Representation Learning with Topology
9. ICML 2024Denoising Autoregressive Representation Learning
10. ICML 2024Differentiable Mapper for Topological Optimization of Data Representation
11. ICML 2024Differentially Private Representation Learning via Image Captioning
12. ICML 2024Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
13. ICML 2024Evolution-Inspired Loss Functions for Protein Representation Learning
14. ICML 2024Feasibility Consistent Representation Learning for Safe Reinforcement Learning
15. ICML 2024Federated Representation Learning in the Under-Parameterized Regime
16. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
17. ICML 2024Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
18. ICML 2024GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
19. ICML 2024Graph2Tac: Online Representation Learning of Formal Math Concepts
20. ICML 2024Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
21. ICML 2024In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
22. ICML 2024Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
23. ICML 2024Learning Graph Representation via Graph Entropy Maximization
24. ICML 2024Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring
25. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
26. ICML 2024LLM-Empowered State Representation for Reinforcement Learning
27. ICML 2024Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
28. ICML 2024Polynomial-based Self-Attention for Table Representation Learning
29. ICML 2024Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
30. ICML 2024Position: The Platonic Representation Hypothesis
31. ICML 2024Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains
32. ICML 2024Recurrent Distance Filtering for Graph Representation Learning
33. ICML 2024Rejuvenating image-GPT as Strong Visual Representation Learners
34. ICML 2024RMIB: Representation Matching Information Bottleneck for Matching Text Representations
35. ICML 2024Robustness of Nonlinear Representation Learning
36. ICML 2024SCoRe: Submodular Combinatorial Representation Learning
37. ICML 2024Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
38. ICML 2024TSLANet: Rethinking Transformers for Time Series Representation Learning
39. ICML 2024UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
40. ICML 2024Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
41. ICML 2024Visual Representation Learning with Stochastic Frame Prediction
42. ICML 2024When Representations Align: Universality in Representation Learning Dynamics

FAQ

How many Deep learning · representation learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

802 in total: 259 in 2023, 177 in 2024, 152 in 2025, 214 in 2026.

How many Deep learning · representation learning papers are at NeurIPS 2026?

NeurIPS 2026 has 59 Deep learning · representation learning papers, versus 54 the year before.

How many Deep learning · representation learning papers are at ICLR 2026?

ICLR 2026 has 39 Deep learning · representation learning papers, versus 37 the year before.

How many Deep learning · representation learning papers are at ICML 2026?

ICML 2026 has 74 Deep learning · representation learning papers, versus 35 the year before.

How many Deep learning · representation learning papers are at CVPR 2026?

CVPR 2026 has 42 Deep learning · representation learning papers, versus 26 the year before.

Which conference publishes the most Deep learning · representation learning papers?

NeurIPS, with 279 papers from 2023 to 2026.