Research map / Learning theory and algorithms / Sample complexity
Statistical analysis of GAN estimators
Proves error bounds for GANs and neural estimators via adversarial losses and duality.
22 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2017–2026) · an approach in Sample complexity, keyword cluster “estimation · estimator · minimax”
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Where it stands
Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.
3 papers in 2023–24 and 2 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 0.9% to 0.6%.
How this is decided
A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.
How it got here
Most cited paper of each year
- 2017 · Dualing GANs (NeurIPS 2017 · 12 citations)
- 2018 · A Convex Duality Framework for GANs (NeurIPS 2018 · 38 citations)
- 2019 · Approximability of Discriminators Implies Diversity in GANs (ICLR 2019 · 35 citations)
- 2020 · What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation (NeurIPS 2020 · 115 citations)
- 2021 · Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space (NeurIPS 2021 · 23 citations)
- 2022 · Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs (ICLR 2022 · 1 citation)
- 2023 · Stabilizing GANs' Training with Brownian Motion Controller (ICML 2023 · 1 citation)
- 2024 · Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes (ICML 2024 · 0 citations)
- 2025 · Approximation and Generalization Abilities of Score-based Neural Network Generative Models for Sub-Gaussian Distributions (NeurIPS 2025 · 0 citations)
- 2026 · Transfer Learning in Nonparametric Regression with Deep ReLU Networks (ICML 2026 · 0 citations)
Earliest papers here
- Dualing GANs (NeurIPS 2017 · 12 citations)
- AdaGAN: Boosting Generative Models (NeurIPS 2017)
- A Convex Duality Framework for GANs (NeurIPS 2018 · 38 citations)
What has been tried
19 papers here report 128 measured changes (a component added, removed or swapped, compared with a baseline): helped 55%, no clear effect 14%, hurt 24%, mixed 6%. Papers mostly publish changes that helped, so "helped" is over-represented.
Recent preprints
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Related approaches
Same keyword cluster
- Minimax estimation rates (109 papers)
- Optimal mean estimation and subsampling (95 papers)
- Density and property estimation (86 papers)
- Distributed estimation under communication limits (49 papers)
Elsewhere in the topic
- Sample complexity of learning distributions (101 papers)
- Statistical-query lower bounds (85 papers)
- Computational thresholds in graphs and structure (84 papers)
- Learning halfspaces under noise (84 papers)
- Robust and surrogate-loss learning bounds (83 papers)
- Sample complexity of ranking and selection (80 papers)
- Learning under log-concave distributions (80 papers)
- PAC learnability theory (79 papers)
Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).