Research map / Probabilistic and scientific modeling / Molecules and proteins
Survival analysis under censoring
Models time-to-event data with copulas, adversarial and likelihood methods handling censoring.
12 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2018–2026) · an approach in Molecules and proteins, keyword cluster “event · point processes · temporal”
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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.
2 papers in 2023–24 and 3 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 0.4% to 0.3%.
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
- 2018 · DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks (AAAI 2018 · 618 citations)
- 2019 · Deep Recurrent Survival Analysis (AAAI 2019 · 112 citations)
- 2020 · X-CAL: Explicit Calibration for Survival Analysis (NeurIPS 2020 · 11 citations)
- 2021 · DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis (AAAI 2021 · 14 citations)
- 2023 · Survival Permanental Processes for Survival Analysis with Time-Varying Covariates (NeurIPS 2023 · 0 citations)
- 2024 · Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees (AAAI 2024 · 7 citations)
- 2026 · Learning Survival Models with Right-Censored Reporting Delays (NeurIPS 2026 · 0 citations)
Earliest papers here
- DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks (AAAI 2018 · 618 citations)
- Adversarial Time-to-Event Modeling (ICML 2018 · 24 citations)
- Multitask Boosting for Survival Analysis with Competing Risks (NeurIPS 2018 · 13 citations)
What has been tried
9 papers here report 75 measured changes (a component added, removed or swapped, compared with a baseline): helped 71%, no clear effect 13%, hurt 8%, mixed 8%. Papers mostly publish changes that helped, so "helped" is over-represented.
Recent preprints
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Related approaches
Same keyword cluster
- Neural point-process models (64 papers)
Elsewhere in the topic
- Generative protein structure design (142 papers)
- Prediction-powered and conformal inference (129 papers)
- Statistical analysis of ML practice (122 papers)
- Neuro-symbolic probabilistic layers (120 papers)
- Structure-based 3D molecule generation (107 papers)
- Sparse graphical and tensor models (97 papers)
- Flow matching generative modeling (97 papers)
- Machine learning for physical simulation (96 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).