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Computational Efficiency

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Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/haoheliu/AudioLDM

공식 코드

AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

https://github.com/haokunchen245/fedpop

공식 코드

FedPop: Federated Population-based Hyperparameter Tuning

https://github.com/haonan3/anchorcontext

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When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training

https://github.com/haoshu2000/tctnn

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Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion Theory

https://github.com/haoxuanli-thu/hcma-unet

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HCMA-UNet: A Hybrid CNN-Mamba UNet with Axial Self-Attention for Efficient Breast Cancer Segmentation

https://github.com/harborsarah/lircdepth

공식 코드

LiRCDepth: Lightweight Radar-Camera Depth Estimation via Knowledge Distillation and Uncertainty Guidance

https://github.com/harshavardhanatg/geometryofsemg

공식 코드

Topology of surface electromyogram signals: hand gesture decoding on Riemannian manifolds

https://github.com/hazdzz/Converter

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Converting Transformers into DGNNs Form

https://github.com/hazyresearch/state-spaces

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Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers

https://github.com/hbyecoding/u-rwkv

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U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKV

https://github.com/helmholtz-ai-energy/f3

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Feed-Forward Optimization With Delayed Feedback for Neural Networks

https://github.com/henry991115/mcfnet

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Multi-scale Cascaded Large-Model for Whole-body ROI Segmentation

https://github.com/henzler/neuraltexture

공식 코드

Learning a Neural 3D Texture Space from 2D Exemplars

https://github.com/hezongyao/diif

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Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image Representation

https://github.com/hezongyao/lmf

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Latent Modulated Function for Computational Optimal Continuous Image Representation

https://github.com/hht1996ok/fastmap

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FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction Framework

https://github.com/hidkim/k2ie

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K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes

https://github.com/hipersimlab/pecann

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An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networks

https://github.com/hisar-research/sionna-nn-receiver-playground

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Novel Deep Neural OFDM Receiver Architectures for LLR Estimation

https://github.com/hits-mbm-dev/grappa

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Grappa -- A Machine Learned Molecular Mechanics Force Field

https://github.com/hkuds/lightgnn

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LightGNN: Simple Graph Neural Network for Recommendation

https://github.com/hkuedl/Latent-Variable-based-Optimization

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Dimension-reduced Optimization of Multi-zone Thermostatically Controlled Loads

https://github.com/hli2020/lps_tip15

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Inner and Inter Label Propagation: Salient Object Detection in the Wild

https://github.com/hlt-mt/fbk-fairseq

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Joint Speech Translation and Named Entity Recognition

https://github.com/hmgoforth/PointNetLK

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PointNetLK: Robust & Efficient Point Cloud Registration using PointNet

https://github.com/hojonathanho/localbitsback

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Compression with Flows via Local Bits-Back Coding

https://github.com/hon-wong/bytevideollm

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Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM

https://github.com/howard-hou/rwkv-ts

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RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks

https://github.com/huaidanquede/PrimeK-Net

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PrimeK-Net: Multi-scale Spectral Learning via Group Prime-Kernel Convolutional Neural Networks for Single Channel Speech Enhancement

https://github.com/huanzhang12/CROWN-Robustness-Certification

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Efficient Neural Network Robustness Certification with General Activation Functions

https://github.com/hudenjear/rploss

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A New Deep-learning-Based Approach For mRNA Optimization: High Fidelity, Computation Efficiency, and Multiple Optimization Factors

https://github.com/hugoladret/epistemic_csc

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Kernel Heterogeneity Improves Sparseness of Natural Images Representations

https://github.com/hui811116/admm-common-info

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Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised Learning

https://github.com/human-analysis/MUXConv

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MUXConv: Information Multiplexing in Convolutional Neural Networks

https://github.com/human9000/nd-mamba2-torch

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Nd-BiMamba2: A Unified Bidirectional Architecture for Multi-Dimensional Data Processing

https://github.com/hurunyi/maskmark

공식 코드

Mask Image Watermarking

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.