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84 papers

Papers

Differentiable Filtering for Learning Hidden Markov Models L4DC 2026 Gated Recurrent Neural Networks with Weighted Time-Delay Feedback AISTATS 2025 GG-SSMs: Graph-Generating State Space Models CVPR 2025 InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis UAI 2025 Online Quantile Regression JMLR 2025 Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era IJCAI 2025 Algorithmic Foundation of Federated Learning with Sequential Data AAAI 2024 Data-efficient Large Vision Models through Sequential Autoregression ICML 2024 Detecting and Identifying Selection Structure in Sequential Data ICML 2024 Modeling Language Tokens as Functionals of Semantic Fields ICML 2024 Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling EACL 2024 A New Modeling Framework for Continuous, Sequential Domains AISTATS 2023 Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning AAAI 2023 Learning Hidden Markov Models When the Locations of Missing Observations are Unknown ICML 2023 Learning to Select Prototypical Parts for Interpretable Sequential Data Modeling AAAI 2023 Max Markov Chain IJCAI 2023 Neural-based classification rule learning for sequential data ICLR 2023 Non-adversarial training of Neural SDEs with signature kernel scores NeurIPS 2023 Revisiting Structured Variational Autoencoders ICML 2023 Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing WACV 2023 Are GANs overkill for NLP? NeurIPS 2022 Learning Structure from the Ground up---Hierarchical Representation Learning by Chunking NeurIPS 2022 Temporally Disentangled Representation Learning NeurIPS 2022 Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks AAAI 2021 Differentiable Segmentation of Sequences ICLR 2021