Image de couverture de livre

Interpretable time series analysis with Gumbel dynamics

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Yiliu, Kim, Timothy Doyeon, Shea-Brown, Eric, Sümbül, Uygar
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Identifying Connectivity Distributions from Neural Dynamics Using Flows
par: Kim, Timothy Doyeon, et autres
Publié: (2026)

Which Quantization Should I Use? A Unified Evaluation of llama.cpp Quantization on Llama-3.1-8B-Instruct
par: Kurt, Uygar
Publié: (2026)

Gumbel-MPNN: Graph Rewiring with Gumbel-Softmax
par: Hoffmann, Marcel, et autres
Publié: (2025)

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
par: Le, Trung, et autres
Publié: (2025)

Refined Detection for Gumbel Watermarking
par: Lattimore, Tor
Publié: (2026)

State-Space NTK Collapse Near Bifurcations
par: Hazelden, James, et autres
Publié: (2026)

A simple connection from loss flatness to compressed neural representations
par: Chen, Shirui, et autres
Publié: (2023)

Gumbel Distillation for Parallel Text Generation
par: Zhang, Chi, et autres
Publié: (2026)

Efficient Connectivity-Preserving Instance Segmentation with Supervoxel-Based Loss Function
par: Grim, Anna, et autres
Publié: (2025)

Feature Structure Distillation with Centered Kernel Alignment in BERT Transferring
par: Jung, Hee-Jun, et autres
Publié: (2022)

QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning
par: Lee, Doyeon, et autres
Publié: (2026)

MAGE: All-[MASK] Block Already Knows Where to Look in Diffusion LLM
par: Kwon, Omin, et autres
Publié: (2026)

Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
par: Niu, Xinlei, et autres
Publié: (2023)

Gumbel Counterfactual Generation From Language Models
par: Ravfogel, Shauli, et autres
Publié: (2024)

DCIts -- Deep Convolutional Interpreter for time series
par: Horvatic, Davor, et autres
Publié: (2025)

The Global Empirical NTK: Self-Referential Bias and Dimensionality of Gradient Descent Learning
par: Hazelden, James, et autres
Publié: (2026)

Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
par: Koo, Jabin, et autres
Publié: (2026)

Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation
par: Tang, Sophia, et autres
Publié: (2025)

Discovering group dynamics in coordinated time series via hierarchical recurrent switching-state models
par: Wojnowicz, Michael T., et autres
Publié: (2024)

Revisiting Tree Search for LLMs: Gumbel and Sequential Halving for Budget-Scalable Reasoning
par: Ugadiarov, Leonid, et autres
Publié: (2026)

KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
par: Hazelden, James, et autres
Publié: (2025)

GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
par: Dadgarnia, Alireza, et autres
Publié: (2026)

Large Pre-trained time series models for cross-domain Time series analysis tasks
par: Kamarthi, Harshavardhan, et autres
Publié: (2023)

Can time series forecasting be automated? A benchmark and analysis
par: Sreedhara, Anvitha Thirthapura, et autres
Publié: (2024)

Conditional Gumbel-Softmax for constrained feature selection with application to node selection in wireless sensor networks
par: Strypsteen, Thomas, et autres
Publié: (2024)

Interpretable mixture of experts for time series prediction under recurrent and non-recurrent conditions
par: Ke, Zemian, et autres
Publié: (2024)

SofT-GRPO: Surpassing Discrete-Token LLM Reinforcement Learning via Gumbel-Reparameterized Soft-Thinking Policy Optimization
par: Zheng, Zhi, et autres
Publié: (2025)

Interpretable facial dynamics as behavioral and perceptual traces of deepfakes
par: Murphy, Timothy Joseph, et autres
Publié: (2026)

NUM2EVENT: Interpretable Event Reasoning from Numerical time-series
par: Feng, Ninghui, et autres
Publié: (2025)

Towards Accurate and Interpretable Time-series Forecasting: A Polynomial Learning Approach
par: Liu, Bo, et autres
Publié: (2026)

TOKON: TOKenization-Optimized Normalization for time series analysis with a large language model
par: Yang, Janghoon
Publié: (2025)

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs
par: Werner, Julia, et autres
Publié: (2023)

Multi-scale hypergraph meets LLMs: Aligning large language models for time series analysis
par: Shang, Zongjiang, et autres
Publié: (2026)

Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series Classification
par: Wen, Yunshi, et autres
Publié: (2024)

Can Differentiable Decision Trees Enable Interpretable Reward Learning from Human Feedback?
par: Kalra, Akansha, et autres
Publié: (2023)

Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation
par: Zarvandi, Maedeh, et autres
Publié: (2025)

Discovering stochastic dynamical equations from biological time series data
par: Nabeel, Arshed, et autres
Publié: (2022)

Machine learning algorithms to predict stroke in China based on causal inference of time series analysis
par: Zheng, Qizhi, et autres
Publié: (2025)

Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosis
par: Yokoyama, Hiroshi, et autres
Publié: (2024)

On time series clustering with k-means
par: Holder, Christopher, et autres
Publié: (2024)