Copertina

Implementation of tangent linear and adjoint models for neural networks based on a compiler library tool

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xiao, Sa, Jing, Hao, Sun, Honglu, Li, Haoyu
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Mathematical Software Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Adaptation of XAI to Auto-tuning for Numerical Libraries
di: Aoki, Shota, et al.
Pubblicazione: (2024)

KHRONOS: a Kernel-Based Neural Architecture for Rapid, Resource-Efficient Scientific Computation
di: Batley, Reza T., et al.
Pubblicazione: (2025)

Int2Int: a framework for mathematics with transformers
di: Charton, François
Pubblicazione: (2025)

$k$-server-bench: Automating Potential Discovery for the $k$-Server Conjecture
di: Brilliantov, Kirill, et al.
Pubblicazione: (2026)

MiniTensor: A Lightweight, High-Performance Tensor Operations Library
di: Sarkar, Soumyadip
Pubblicazione: (2026)

A Lie Group Approach to Riemannian Batch Normalization
di: Chen, Ziheng, et al.
Pubblicazione: (2024)

cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
di: Qiu, Yixuan
Pubblicazione: (2026)

Virtual Parameter Sharpening: Dynamic Low-Rank Perturbations for Inference-Time Reasoning Enhancement
di: Kublashvili, Saba
Pubblicazione: (2025)

TopoX: A Suite of Python Packages for Machine Learning on Topological Domains
di: Hajij, Mustafa, et al.
Pubblicazione: (2024)

Guiding the retraining of convolutional neural networks against adversarial inputs
di: López, Francisco Durán, et al.
Pubblicazione: (2022)

On Stochastic Rounding with Few Random Bits
di: Fitzgibbon, Andrew, et al.
Pubblicazione: (2025)

Scorch: A Library for Sparse Deep Learning
di: Yan, Bobby, et al.
Pubblicazione: (2024)

UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
di: Han, Xi, et al.
Pubblicazione: (2024)

Learning optimal objective values for MILP
di: Scavuzzo, Lara, et al.
Pubblicazione: (2024)

TurboSAT: Gradient-Guided Boolean Satisfiability Accelerated on GPU-CPU Hybrid System
di: Dai, Steve, et al.
Pubblicazione: (2025)

Machine learning based radiative parameterization scheme and its performance in operational reforecast experiments
di: Jing, Hao, et al.
Pubblicazione: (2026)

Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification
di: Wu, Zehao, et al.
Pubblicazione: (2025)

An Open-Source Framework for Efficient Numerically-Tailored Computations
di: Ledoux, Louis, et al.
Pubblicazione: (2024)

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods
di: Deotale, Rushikesh, et al.
Pubblicazione: (2026)

Dimensionality reduction for homological stability and global structure preservation
di: Kolpakov, Alexander, et al.
Pubblicazione: (2025)

China Regional 3km Downscaling Based on Residual Corrective Diffusion Model
di: Sun, Honglu, et al.
Pubblicazione: (2025)

Does Few-Shot Learning Help LLM Performance in Code Synthesis?
di: Xu, Derek, et al.
Pubblicazione: (2024)

Graph Neural Networks based Log Anomaly Detection and Explanation
di: Li, Zhong, et al.
Pubblicazione: (2023)

Unlocking FedNL: Self-Contained Compute-Optimized Implementation
di: Burlachenko, Konstantin, et al.
Pubblicazione: (2024)

MIST-RL: Mutation-based Incremental Suite Testing via Reinforcement Learning
di: Zhu, Sicheng, et al.
Pubblicazione: (2026)

Structural perspective on constraint-based learning of Markov networks
di: Korhonen, Tuukka, et al.
Pubblicazione: (2024)

What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach
di: Wu, Xingfang, et al.
Pubblicazione: (2024)

LLM-based Content Classification Approach for GitHub Repositories by the README Files
di: Mehmood, Malik Uzair, et al.
Pubblicazione: (2025)

NNTile: a machine learning framework capable of training extremely large GPT language models on a single node
di: Mikhalev, Aleksandr, et al.
Pubblicazione: (2025)

Exploring Pass-Rate Reward in Reinforcement Learning for Code Generation
di: Li, Xin-Ye, et al.
Pubblicazione: (2026)

daVinci-Agency: Unlocking Long-Horizon Agency Data-Efficiently
di: Jiang, Mohan, et al.
Pubblicazione: (2026)

Effective backdoor attack on graph neural networks in link prediction tasks
di: Dai, Jiazhu, et al.
Pubblicazione: (2024)

LiCoEval: Evaluating LLMs on License Compliance in Code Generation
di: Xu, Weiwei, et al.
Pubblicazione: (2024)

CausalVerse: Benchmarking Causal Representation Learning with Configurable High-Fidelity Simulations
di: Chen, Guangyi, et al.
Pubblicazione: (2025)

Mutation-Guided LLM-based Test Generation at Meta
di: Foster, Christopher, et al.
Pubblicazione: (2025)

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations
di: Wang, Jiaping, et al.
Pubblicazione: (2025)

RBT4DNN: Requirements-based Testing of Neural Networks
di: Mozumder, Nusrat Jahan, et al.
Pubblicazione: (2025)

Code Generation by Differential Test Time Scaling
di: He, Yifeng, et al.
Pubblicazione: (2026)

CSR-Bench: Benchmarking LLM Agents in Deployment of Computer Science Research Repositories
di: Xiao, Yijia, et al.
Pubblicazione: (2025)

Insights into resource utilization of code small language models serving with runtime engines and execution providers
di: Durán, Francisco, et al.
Pubblicazione: (2024)