{"total":35,"rows":[{"id":"2106.00154","title":"Explanations for Monotonic Classifiers","created":"2021-06-01","cited_by_count":39,"area":null},{"id":"2205.11775","title":"Constrained Monotonic Neural Networks","created":"2022-05-24","cited_by_count":32,"area":null},{"id":"2209.06257","title":"A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge","created":"2022-09-13","cited_by_count":31,"area":null},{"id":"2103.15624","title":"Shape-constrained Symbolic Regression -- Improving Extrapolation with Prior Knowledge","created":"2021-03-29","cited_by_count":27,"area":null},{"id":"2109.01904","title":"Estimating Categorical Counterfactuals via Deep Twin Networks","created":"2021-09-04","cited_by_count":19,"area":null},{"id":"2105.11363","title":"Learning Security Classifiers with Verified Global Robustness Properties","created":"2021-05-24","cited_by_count":14,"area":null},{"id":"2310.02600","title":"Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks","created":"2023-10-04","cited_by_count":13,"area":null},{"id":"2201.12848","title":"Deep Non-Crossing Quantiles through the Partial Derivative","created":"2022-01-30","cited_by_count":12,"area":null},{"id":"2111.12490","title":"Matching Learned Causal Effects of Neural Networks with Domain Priors","created":"2021-11-24","cited_by_count":10,"area":null},{"id":"2207.05275","title":"Size and depth of monotone neural networks: interpolation and approximation","created":"2022-07-12","cited_by_count":10,"area":null},{"id":"2110.00535","title":"A Cram\\'er Distance perspective on Quantile Regression based Distributional Reinforcement Learning","created":"2021-10-01","cited_by_count":8,"area":null},{"id":"2505.02537","title":"Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations","created":"2025-05-05","cited_by_count":8,"area":null},{"id":"2107.09546","title":"Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions","created":"2021-07-20","cited_by_count":7,"area":null},{"id":"2108.12100","title":"A framework for massive scale personalized promotion","created":"2021-08-27","cited_by_count":4,"area":null},{"id":"2303.01141","title":"DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction","created":"2023-03-02","cited_by_count":4,"area":null},{"id":"2202.01940","title":"Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks","created":"2022-02-04","cited_by_count":3,"area":null},{"id":"2209.13851","title":"Shape-constrained Symbolic Regression with NSGA-III","created":"2022-09-28","cited_by_count":3,"area":null},{"id":"2202.01277","title":"Global Optimization Networks","created":"2022-02-02","cited_by_count":2,"area":null},{"id":"2206.11172","title":"Neural Inverse Transform Sampler","created":"2022-06-22","cited_by_count":2,"area":null},{"id":"2209.10956","title":"XClusters: Explainability-first Clustering","created":"2022-09-22","cited_by_count":2,"area":null},{"id":"2102.05135","title":"Regularization Strategies for Quantile Regression","created":"2021-02-09","cited_by_count":1,"area":null},{"id":"2503.09592","title":"Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors","created":"2025-03-12","cited_by_count":1,"area":null},{"id":"2507.07738","title":"Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks","created":"2025-07-10","cited_by_count":1,"area":null},{"id":"2601.06730","title":"Why are there many equally good models? An Anatomy of the Rashomon Effect","created":"2026-01-11","cited_by_count":1,"area":null},{"id":"2606.17886","title":"Monotonic Kolmogorov-Arnold Networks: A Theoretical and Empirical Study of Monotonicity as an Inductive Bias","created":"2026-06-16","cited_by_count":1,"area":null},{"id":"2504.08415","title":"Constrained Machine Learning Through Hyperspherical Representation","created":"2025-04-11","cited_by_count":0,"area":null},{"id":"2507.02169","title":"Responsiveness Verification: Will Predictions Change? How Much? How Often?","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2509.08467","title":"An Interpretable Deep Learning Model for General Insurance Pricing","created":"2025-09-10","cited_by_count":0,"area":null},{"id":"2509.22931","title":"MonoCon: A general framework for learning ultra-compact high-fidelity representations using monotonicity constraints","created":"2025-09-26","cited_by_count":0,"area":null},{"id":"2511.13756","title":"Multi-Horizon Time Series Forecasting of non-parametric CDFs with Deep Lattice Networks","created":"2025-11-14","cited_by_count":0,"area":null},{"id":"2603.01890","title":"Resolving Blind Inverse Problems under Dynamic Range Compression via Structured Forward Operator Modeling","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2604.16821","title":"R&F-Inventory: A Large-Scale Dataset for Monotonic Inventory Estimation in Reach and Frequency Advertising","created":"2026-04-18","cited_by_count":0,"area":null},{"id":"2608.08003","title":"The Spectral Neuron","created":"2026-08-08","cited_by_count":0,"area":null},{"id":"2608.21059","title":"The Cost of a Physics Prior Is Bounded by the Ablation Gap","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2610.00858","title":"Fixing a Model That Learned Worse Cancer Means Lower Risk: Monotonic Constraints in Bladder Cancer Recurrence Prediction","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}