:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteur principal:	Akhtar, Sheikh Waqas
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2312.01657
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder
par: Akhtar, Sheikh Waqas
Publié: (2024)

SPIN-ODE: Stiff Physics-Informed Neural ODE for Chemical Reaction Rate Estimation
par: Peng, Wenqing, et autres
Publié: (2025)

A comparative study of NeuralODE and Universal ODE approaches to solving Chandrasekhar White Dwarf equation
par: Martinez, Raymundo Vazquez, et autres
Publié: (2024)

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples
par: Vouitsis, Noël, et autres
Publié: (2024)

Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting
par: Liu, Peiyuan, et autres
Publié: (2024)

Faster Convergence for Transformer Fine-tuning with Line Search Methods
par: Kenneweg, Philip, et autres
Publié: (2024)

A Neural ODE Approach to Aircraft Flight Dynamics Modelling
par: Jarry, Gabriel, et autres
Publié: (2025)

Tuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization
par: Hinterleitner, Alexander, et autres
Publié: (2025)

Towards Faster Training of Diffusion Models: An Inspiration of A Consistency Phenomenon
par: Xu, Tianshuo, et autres
Publié: (2024)

Toward a Unified Lyapunov-Certified ODE Convergence Analysis of Smooth Q-Learning with p-Norms
par: Lee, Donghwan, et autres
Publié: (2024)

Wavelet-Enhanced Neural ODE and Graph Attention for Interpretable Energy Forecasting
par: Joy, Usman Gani
Publié: (2025)

Automated Discovery of Conservation Laws via Hybrid Neural ODE-Transformers
par: Doshi, Vivan
Publié: (2025)

Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
par: Tong, Anh, et autres
Publié: (2025)

Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning
par: Han, Chao, et autres
Publié: (2026)

LASS-ODE: Scaling ODE Computations to Connect Foundation Models with Dynamical Physical Systems
par: Li, Haoran, et autres
Publié: (2026)

Bridging Neural ODE and ResNet: A Formal Error Bound for Safety Verification
par: Sayed, Abdelrahman Sayed, et autres
Publié: (2025)

Latent Neural-ODE for Model-Informed Precision Dosing: Overcoming Structural Assumptions in Pharmacokinetics
par: Maurel, Benjamin, et autres
Publié: (2026)

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
par: Kim, Dongjun, et autres
Publié: (2023)

BULL-ODE: Bullwhip Learning with Neural ODEs and Universal Differential Equations under Stochastic Demand
par: Naik, Nachiket N., et autres
Publié: (2025)

Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph
par: Wan, Guancheng, et autres
Publié: (2024)

Learning to be Reproducible: Custom Loss Design for Robust Neural Networks
par: Ahmed, Waqas, et autres
Publié: (2026)

Unlocking the Potential of Continual Model Merging: An ODE Perspective
par: Lin, Lihong, et autres
Publié: (2026)

Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
par: Deng, Yichuan, et autres
Publié: (2024)

Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks
par: Liu, Cong, et autres
Publié: (2024)

Consistency of Neural Causal Partial Identification
par: Tan, Jiyuan, et autres
Publié: (2024)

The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
par: Liu, Shuze Daniel, et autres
Publié: (2024)

Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions
par: Choi, Jinyoung, et autres
Publié: (2025)

RL for Consistency Models: Faster Reward Guided Text-to-Image Generation
par: Oertell, Owen, et autres
Publié: (2024)

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
par: Chen, Xin, et autres
Publié: (2025)

Global Convergence in Neural ODEs: Impact of Activation Functions
par: Gao, Tianxiang, et autres
Publié: (2025)

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices
par: Liu, Xin, et autres
Publié: (2026)

A study of Universal ODE approaches to predicting soil organic carbon
par: V. V, Satyanarayana Raju G., et autres
Publié: (2025)

Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning
par: Wang, Xiaoyi, et autres
Publié: (2026)

Modeling chaotic Lorenz ODE System using Scientific Machine Learning
par: Kashyap, Sameera S, et autres
Publié: (2024)

FRoD: Full-Rank Efficient Fine-Tuning with Rotational Degrees for Fast Convergence
par: Wan, Guoan, et autres
Publié: (2025)

Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE
par: Hashimoto, Koji, et autres
Publié: (2024)

ANO : Faster is Better in Noisy Landscape
par: Kegreisz, Adrien
Publié: (2025)

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning
par: Xie, Zhen-Hao, et autres
Publié: (2026)

Gradient Flow Convergence Guarantee for General Neural Network Architectures
par: Jakhmola, Yash
Publié: (2025)

On the Convergence and Size Transferability of Continuous-depth Graph Neural Networks
par: Yan, Mingsong, et autres
Publié: (2025)