Showing 1–20 of 21 results
/ Date/ Name
Nov 30, 2020A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time SeriesSep 30, 2019Black-box Adversarial Attacks with Bayesian OptimizationFeb 7, 2020Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network ClassificationJul 23, 2021Heteroscedastic Temporal Variational Autoencoder For Irregular Time SeriesDec 3, 2018Modeling Irregularly Sampled Clinical Time SeriesJul 13, 2020Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget RegimesSep 13, 2019Interpolation-Prediction Networks for Irregularly Sampled Time SeriesMar 24, 2020Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality PredictionJan 25, 2021Multi-Time Attention Networks for Irregularly Sampled Time SeriesSep 20, 2023Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video UnderstandingDec 6, 2024CompCap: Improving Multimodal Large Language Models with Composite CaptionsApr 8, 2025Transfer between Modalities with MetaQueriesApr 11, 2024Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMsFeb 18, 2026Xray-Visual Models: Scaling Vision models on Industry Scale DataOct 6, 2025Think Then Embed: Generative Context Improves Multimodal EmbeddingDec 26, 2023Universal Pyramid Adversarial Training for Improved ViT PerformanceAug 31, 2023The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language VariantsOct 8, 2020Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial AttacksAug 21, 2025StreamMem: Query-Agnostic KV Cache Memory for Streaming Video UnderstandingMar 2, 2025A Simple and Effective Reinforcement Learning Method for Text-to-Image Diffusion Fine-tuning