| DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging Load | Feb 21, 2024 | DenoisingLoad Forecasting | CodeCode Available | 1 | 5 |
| Diffusion Auto-regressive Transformer for Effective Self-supervised Time Series Forecasting | Oct 8, 2024 | DecoderDenoising | CodeCode Available | 1 | 5 |
| AGNet: Weighing Black Holes with Machine Learning | Nov 30, 2020 | BIG-bench Machine LearningTime Series | CodeCode Available | 1 | 5 |
| Diffusion Generative Models in Infinite Dimensions | Dec 1, 2022 | Time SeriesTime Series Analysis | CodeCode Available | 1 | 5 |
| Adaptive Conformal Predictions for Time Series | Feb 15, 2022 | Conformal PredictionDecision Making | CodeCode Available | 1 | 5 |
| Backdoor Attacks on Time Series: A Generative Approach | Nov 15, 2022 | Time SeriesTime Series Analysis | CodeCode Available | 1 | 5 |
| Accelerating Recurrent Neural Networks for Gravitational Wave Experiments | Jun 26, 2021 | High-Level SynthesisTime Series | CodeCode Available | 1 | 5 |
| AGNet: Weighing Black Holes with Deep Learning | Aug 17, 2021 | Deep LearningTime Series | CodeCode Available | 1 | 5 |
| Badgers: generating data quality deficits with Python | Jul 10, 2023 | Time Series | CodeCode Available | 1 | 5 |
| Dimensionality reduction to maximize prediction generalization capability | Mar 1, 2020 | Dimensionality ReductionPrediction | CodeCode Available | 1 | 5 |
| DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts | Jun 13, 2024 | ManagementMixture-of-Experts | CodeCode Available | 1 | 5 |
| BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis | Oct 31, 2023 | Contrastive LearningSelf-Supervised Learning | CodeCode Available | 1 | 5 |
| Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation | Jan 9, 2025 | Test-time AdaptationTime Series | CodeCode Available | 1 | 5 |
| Discovering Predictable Latent Factors for Time Series Forecasting | Mar 18, 2023 | Time SeriesTime Series Forecasting | CodeCode Available | 1 | 5 |
| Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting | Feb 22, 2023 | Time SeriesTime Series Analysis | CodeCode Available | 1 | 5 |
| Disjoint-CNN for Multivariate Time Series Classification | Jan 20, 2022 | ClassificationDeep Learning | CodeCode Available | 1 | 5 |
| Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark | Dec 15, 2023 | Activity RecognitionDomain Adaptation | CodeCode Available | 1 | 5 |
| BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition | Aug 28, 2023 | Computational EfficiencyGaussian Processes | CodeCode Available | 1 | 5 |
| Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series | Feb 7, 2024 | Prediction IntervalsTime Series | CodeCode Available | 1 | 5 |
| Domain Adaptation for Time Series Under Feature and Label Shifts | Feb 6, 2023 | Domain AdaptationTime Series | CodeCode Available | 1 | 5 |
| Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting | Jul 6, 2020 | Graph GenerationGraph Neural Network | CodeCode Available | 1 | 5 |
| Benchmarking Deep Learning Interpretability in Time Series Predictions | Oct 26, 2020 | BenchmarkingDeep Learning | CodeCode Available | 1 | 5 |
| Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown | Feb 21, 2021 | DecoderTime Series | CodeCode Available | 1 | 5 |
| Differentiable Compositional Kernel Learning for Gaussian Processes | Jun 12, 2018 | Bayesian OptimizationGaussian Processes | CodeCode Available | 1 | 5 |
| Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting | Feb 18, 2025 | DisentanglementTime Series | CodeCode Available | 1 | 5 |
