| Non-Autoregressive Diffusion-based Temporal Point Processes for Continuous-Time Long-Term Event Prediction | Nov 2, 2023 | DenoisingPoint Processes | CodeCode Available | 0 | 5 |
| Online Estimation and Community Detection of Network Point Processes for Event Streams | Sep 3, 2020 | Community DetectionOnline Community Detection | CodeCode Available | 0 | 5 |
| Kronecker Determinantal Point Processes | May 26, 2016 | Point ProcessesStochastic Optimization | CodeCode Available | 0 | 5 |
| DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization | Jul 26, 2022 | Point Processes | CodeCode Available | 0 | 5 |
| A topological data analysis based classification method for multiple measurements | Apr 5, 2019 | Classificationfeature selection | CodeCode Available | 0 | 5 |
| In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point Processes | Sep 24, 2019 | Abstractive Text SummarizationDiversity | CodeCode Available | 0 | 5 |
| Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions | Sep 23, 2019 | Dynamic Link PredictionLink Prediction | CodeCode Available | 0 | 5 |
| PCA for Point Processes | Apr 30, 2024 | Point Processes | CodeCode Available | 0 | 5 |
| Intensity-free Integral-based Learning of Marked Temporal Point Processes | Aug 4, 2023 | Point Processes | CodeCode Available | 0 | 5 |
| PoPPy: A Point Process Toolbox Based on PyTorch | Oct 23, 2018 | Point Processes | CodeCode Available | 0 | 5 |
| Hawkes Process Based on Controlled Differential Equations | May 9, 2023 | Irregular Time SeriesPoint Processes | CodeCode Available | 0 | 5 |
| Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes | Jan 9, 2024 | Conformal PredictionPoint Processes | CodeCode Available | 0 | 5 |
| Fully Neural Network based Model for General Temporal Point Processes | May 23, 2019 | Point ProcessesTime Series | CodeCode Available | 0 | 5 |
| Row-clustering of a Point Process-valued Matrix | Oct 4, 2021 | ClusteringPoint Processes | CodeCode Available | 0 | 5 |
| A weak MLMC scheme for Lévy-copula-driven SDEs with applications to the pricing of credit, equity and interest rate derivatives | Nov 4, 2022 | Point Processes | CodeCode Available | 0 | 5 |
| Deep Neyman-Scott Processes | Nov 6, 2021 | Point Processes | CodeCode Available | 0 | 5 |
| Deep Random Splines for Point Process Intensity Estimation of Neural Population Data | Mar 6, 2019 | Dimensionality ReductionGaussian Processes | CodeCode Available | 0 | 5 |
| Intensity-Free Learning of Temporal Point Processes | Sep 26, 2019 | Point Processes | CodeCode Available | 0 | 5 |
| Deep Reinforcement Learning of Marked Temporal Point Processes | May 23, 2018 | Deep Reinforcement LearningMarketing | CodeCode Available | 0 | 5 |
| Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain | Sep 29, 2023 | Computational EfficiencyPoint Processes | CodeCode Available | 0 | 5 |
| Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel | Feb 26, 2021 | Bayesian OptimizationPoint Processes | CodeCode Available | 0 | 5 |
| An information-theoretic framework to measure the dynamic interaction between neural spike trains | Dec 15, 2020 | Point Processes | CodeCode Available | 0 | 5 |
| Lazy and Fast Greedy MAP Inference for Determinantal Point Process | Jun 13, 2022 | Point Processes | CodeCode Available | 0 | 5 |
| Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport | Jan 24, 2022 | Point ProcessesUncertainty Quantification | CodeCode Available | 0 | 5 |
| Better Highlighting: Creating Sub-Sentence Summary Highlights | Oct 20, 2020 | Point ProcessesSentence | CodeCode Available | 0 | 5 |
| Stopping Methods for Technology Assisted Reviews based on Point Processes | Nov 14, 2023 | Point ProcessesTAR | CodeCode Available | 0 | 5 |
| Exact sampling of determinantal point processes with sublinear time preprocessing | May 31, 2019 | Point Processes | CodeCode Available | 0 | 5 |
| Faster Greedy MAP Inference for Determinantal Point Processes | Mar 9, 2017 | Point Processes | CodeCode Available | 0 | 5 |
| Entropic Trace Estimates for Log Determinants | Apr 24, 2017 | Gaussian ProcessesPoint Processes | CodeCode Available | 0 | 5 |
| Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes | Jan 29, 2022 | Decision MakingModel-based Reinforcement Learning | CodeCode Available | 0 | 5 |
| Evaluating Uncertainty in Deep Gaussian Processes | Apr 24, 2025 | Gaussian ProcessesPoint Processes | CodeCode Available | 0 | 5 |
| Fast Estimation of Causal Interactions using Wold Processes | Jul 12, 2018 | Point Processes | CodeCode Available | 0 | 5 |
| Determinantal thinning of point processes with network learning applications | Oct 9, 2018 | Point ProcessesScheduling | CodeCode Available | 0 | 5 |
| DPPy: Sampling DPPs with Python | Sep 19, 2018 | BIG-bench Machine LearningDiversity | CodeCode Available | 0 | 5 |
| Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series | Apr 30, 2020 | Causal InferencePoint Processes | CodeCode Available | 0 | 5 |
| Differentiable Adversarial Attacks for Marked Temporal Point Processes | Jan 17, 2025 | Adversarial AttackPoint Processes | CodeCode Available | 0 | 5 |
| A Faster Sampler for Discrete Determinantal Point Processes | Oct 31, 2022 | Point Processes | CodeCode Available | 0 | 5 |
| Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling | Mar 6, 2020 | DiversityPoint Processes | CodeCode Available | 0 | 5 |
| Exact Bayesian Gaussian Cox Processes Using Random Integral | Jun 28, 2024 | Data AugmentationPoint Processes | CodeCode Available | 0 | 5 |
| Efficient Inference in Multi-task Cox Process Models | May 24, 2018 | Gaussian ProcessesPoint Processes | CodeCode Available | 0 | 5 |
| Determinantal point processes for machine learning | Jul 25, 2012 | BIG-bench Machine LearningPoint Processes | CodeCode Available | 0 | 5 |
| Determinantal Point Processes for Coresets | Mar 23, 2018 | Point Processesregression | CodeCode Available | 0 | 5 |
| Active Mini-Batch Sampling using Repulsive Point Processes | Apr 8, 2018 | Point Processes | CodeCode Available | 0 | 5 |
| Diversity-Aware Batch Active Learning for Dependency Parsing | Apr 28, 2021 | Active LearningDependency Parsing | CodeCode Available | 0 | 5 |
| Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes | Dec 5, 2022 | Computational EfficiencyGraph Representation Learning | CodeCode Available | 0 | 5 |
| SimHawNet: A Modified Hawkes Process for Temporal Network Simulation | Mar 14, 2022 | BIG-bench Machine LearningLink Prediction | CodeCode Available | 0 | 5 |
| Bayesian experimental design using regularized determinantal point processes | Jun 10, 2019 | Experimental DesignPoint Processes | CodeCode Available | 0 | 5 |
| Diverse Online Feature Selection | Jun 12, 2018 | Diversityfeature selection | CodeCode Available | 0 | 5 |
| Breaking hypothesis testing for failure rates | Jan 13, 2020 | Point ProcessesTwo-sample testing | CodeCode Available | 0 | 5 |
| Diversity Networks: Neural Network Compression Using Determinantal Point Processes | Nov 16, 2015 | DiversityNeural Network Compression | CodeCode Available | 0 | 5 |
