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

https://github.com/dqwang122/thinkhub

공식 코드

TypedThinker: Typed Thinking Improves Large Language Model Reasoning

https://github.com/drlxj/camdiff

공식 코드

CamDiff: Camouflage Image Augmentation via Diffusion Model

https://github.com/drorsimon/CSCNet

공식 코드

Rethinking the CSC Model for Natural Images

https://github.com/dsanmartin/chilean-bills-classification

공식 코드

A Deep Learning Model for Chilean Bills Classification

https://github.com/dtolpin/rmi-case-studies

공식 코드

A Renewal Model of Intrusion

https://github.com/dtuzi123/expansion-graph-model

공식 코드

Lifelong Generative Modelling Using Dynamic Expansion Graph Model

https://github.com/duchenzhuang/flowencrypt

공식 코드

Secure Data Sharing With Flow Model

https://github.com/duguodong7/pcb-merging

공식 코드

Parameter Competition Balancing for Model Merging

https://github.com/dvlab-research/LLMGA

공식 코드

LLMGA: Multimodal Large Language Model based Generation Assistant

https://github.com/dvlab-research/lisa

공식 코드

LISA: Reasoning Segmentation via Large Language Model

https://github.com/dwhou/emdc-pytorch

공식 코드

Learning an Efficient Multimodal Depth Completion Model

https://github.com/dwlmt/knowledgeable-stories

공식 코드

A Temporal Variational Model for Story Generation

https://github.com/dwslab/melt

공식 코드

OAEI Machine Learning Dataset for Online Model Generation

https://github.com/dyc941126/gat-pcm

공식 코드

Pretrained Cost Model for Distributed Constraint Optimization Problems

https://github.com/dylan-goetting/Newsvendor-RL

공식 코드

Newsvendor Model with Deep Reinforcement Learning

https://github.com/dzachariah/counterfactual

공식 코드

Model-Robust Counterfactual Prediction Method

https://github.com/easeonway/explainable-causal-reinforcement-learning

공식 코드

Explainable Reinforcement Learning via a Causal World Model

https://github.com/ebagdasa/differential-privacy-vs-fairness

공식 코드

Differential Privacy Has Disparate Impact on Model Accuracy

https://github.com/ebennequin/few-shot-open-set

공식 코드

Model-Agnostic Few-Shot Open-Set Recognition

https://github.com/eboix/theory-of-model-distillation

공식 코드

Towards a theory of model distillation

https://github.com/ebprado/MOTR-BART

공식 코드

Bayesian Additive Regression Trees with Model Trees

https://github.com/ecs-vlc/torchbearer

공식 코드

Torchbearer: A Model Fitting Library for PyTorch

https://github.com/edchengg/model_selection

공식 코드

Model Selection for Cross-Lingual Transfer

https://github.com/edgeslab/hpe-ltm

공식 코드

Heterogeneous Peer Effects in the Linear Threshold Model

https://github.com/edibert4imagemanipulation/edibert

공식 코드

EdiBERT, a generative model for image editing

https://github.com/edmundmills/almanacs

공식 코드

ALMANACS: A Simulatability Benchmark for Language Model Explainability

https://github.com/eduardacaldeira/compression_bias_survey

공식 코드

Model Compression Techniques in Biometrics Applications: A Survey

https://github.com/eduardoramosp/macknet

공식 코드

Mack-Net model: Blending Mack's model with Recurrent Neural Networks

https://github.com/efficientmoe/moe-infinity

공식 코드

MoE-Infinity: Efficient MoE Inference on Personal Machines with Sparsity-Aware Expert Cache

https://github.com/ege-erdogan/unsplit

공식 코드

UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning

https://github.com/ehaleva/riq

공식 코드

Rotation Invariant Quantization for Model Compression

https://github.com/ehsanaghaei/SecureBERT

공식 코드

SecureBERT: A Domain-Specific Language Model for Cybersecurity

https://github.com/ehsk/CHF-TopoResolver

공식 코드

A Coherent Unsupervised Model for Toponym Resolution

https://github.com/ejmichaud/quantization-model

공식 코드

The Quantization Model of Neural Scaling

https://github.com/el-hult/lal

공식 코드

Diagnostic Tool for Out-of-Sample Model Evaluation

https://github.com/eladhi/VI-Glow

공식 코드

Color Visual Illusions: A Statistics-based Computational Model

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