Copertina

Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lee, Dohoon, Park, Jaehyun, Kim, Hyunwoo J., Lee, Kyogu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence I.2.6; I.5.1; F.1.1
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Emergence of Quantised Representations Isolated to Anisotropic Functions
di: Bird, George
Pubblicazione: (2025)

SecureV2X: An Efficient and Privacy-Preserving System for Vehicle-to-Everything (V2X) Applications
di: Lee, Joshua, et al.
Pubblicazione: (2025)

Information-Theoretic Quality Metric of Low-Dimensional Embeddings
di: Gutiérrez-Bernal, Sebastián, et al.
Pubblicazione: (2025)

Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
di: Zhang, Xu, et al.
Pubblicazione: (2025)

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization
di: Jiang, Xiantao
Pubblicazione: (2026)

Tricks and Plug-ins for Gradient Boosting with Transformers
di: Fang, Biyi, et al.
Pubblicazione: (2025)

Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification
di: Rottenwalter, Georg, et al.
Pubblicazione: (2025)

Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method
di: Priezzhev, I. I., et al.
Pubblicazione: (2025)

Advancements in synthetic data extraction for industrial injection molding
di: Rottenwalter, Georg, et al.
Pubblicazione: (2025)

Predicting Future Actions of Reinforcement Learning Agents
di: Chung, Stephen, et al.
Pubblicazione: (2024)

Quantum inspired qubit qutrit neural networks for real time financial forecasting
di: Bakshi, Kanishk, et al.
Pubblicazione: (2026)

Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual Explanations
di: Carrow, Stephen, et al.
Pubblicazione: (2024)

GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
di: Liu, Zehao, et al.
Pubblicazione: (2025)

Out of Distribution Detection for Efficient Continual Learning in Quality Prediction for Arc Welding
di: Hahn, Yannik, et al.
Pubblicazione: (2025)

Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
di: Febrinanto, Falih Gozi, et al.
Pubblicazione: (2023)

Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization
di: Zarifis, Stelios, et al.
Pubblicazione: (2025)

Learning to Land Anywhere: Transferable Generative Models for Aircraft Trajectories
di: Larsen, Olav Finne Praesteng, et al.
Pubblicazione: (2025)

LLM Performance Predictors: Learning When to Escalate in Hybrid Human-AI Moderation Systems
di: Bachar, Or, et al.
Pubblicazione: (2026)

Augmenting Replay in World Models for Continual Reinforcement Learning
di: Yang, Luke, et al.
Pubblicazione: (2024)

MMM: Quantum-Chemical Molecular Representation Learning for Combinatorial Drug Recommendation
di: Kwon, Chongmyung, et al.
Pubblicazione: (2025)

Diffusion-Based Forecasting for Uncertainty-Aware Model Predictive Control
di: Zarifis, Stelios, et al.
Pubblicazione: (2025)

RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
di: Lv, Haochen, et al.
Pubblicazione: (2025)

AdaCap: An Adaptive Contrastive Approach for Small-Data Neural Networks
di: Belucci, Bruno, et al.
Pubblicazione: (2025)

DGTEN: A Robust Deep Gaussian based Graph Neural Network for Dynamic Trust Evaluation with Uncertainty-Quantification Support
di: Usman, Muhammad, et al.
Pubblicazione: (2025)

Audience Amplified: Virtual Audiences in Asynchronously Performed AR Theater
di: Kim, You-Jin, et al.
Pubblicazione: (2025)

multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data
di: Loza, Andrew J., et al.
Pubblicazione: (2025)

Contrastive and Multi-Task Learning on Noisy Brain Signals with Nonlinear Dynamical Signatures
di: Ghosh, Sucheta, et al.
Pubblicazione: (2026)

In-situ Autoguidance: Eliciting Self-Correction in Diffusion Models
di: Gu, Enhao, et al.
Pubblicazione: (2025)

Regularisation in neural networks: a survey and empirical analysis of approaches
di: Opperman, Christiaan P., et al.
Pubblicazione: (2026)

When is dataset cartography ineffective? Using training dynamics does not improve robustness against Adversarial SQuAD
di: Mandal, Paul K.
Pubblicazione: (2025)

A Self-explainable Model of Long Time Series by Extracting Informative Structured Causal Patterns
di: Wang, Ziqian, et al.
Pubblicazione: (2025)

Less is More: Learning Graph Tasks with Just LLMs
di: Shirai, Sola, et al.
Pubblicazione: (2025)

Optimizing Inference in Transformer-Based Models: A Multi-Method Benchmark
di: Ho, Siu Hang, et al.
Pubblicazione: (2025)

Efficient Morphology-Control Co-Design via Stackelberg Proximal Policy Optimization
di: Dai, Yanning, et al.
Pubblicazione: (2026)

Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach
di: Nelson-Archer, Adam, et al.
Pubblicazione: (2025)

Conformal PM2.5 Mapping Under Spatial Covariate Shift: Satellite-Reanalysis Fusion for Africa's Green Industrial Transition
di: Adjei, Yaw Osei, et al.
Pubblicazione: (2026)

Inter-Series Transformer: Attending to Products in Time Series Forecasting
di: Cristian, Rares, et al.
Pubblicazione: (2024)

A Hybrid Model for Stock Market Forecasting: Integrating News Sentiment and Time Series Data with Graph Neural Networks
di: Sadek, Nader, et al.
Pubblicazione: (2025)

Bandwidth Selectors on Semiparametric Bayesian Networks
di: Alejandre, Victor, et al.
Pubblicazione: (2025)

Label Smoothing is a Pragmatic Information Bottleneck
di: Kudo, Sota
Pubblicazione: (2025)