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Prediction

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

https://github.com/herbps10/adaptiveconformal

A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

https://github.com/hieu2906090/deep-learning-in-js

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

https://github.com/horizonrobotics/gump

Trajeglish: Traffic Modeling as Next-Token Prediction

https://github.com/houda96/imagi-filter

ImagiFilter: A resource to enable the semi-automatic mining of images at scale

https://github.com/hsd1503/resnet1d

HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units

https://github.com/huang229/auto_tooth_arrangement

Mesh R-CNN

https://github.com/huggingface/transformers

ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training

https://github.com/huseinzol05/malaya-speech

FastPitch: Parallel Text-to-speech with Pitch Prediction

https://github.com/huzi96/PS-RNN-HEVC

Progressive Spatial Recurrent Neural Network for Intra Prediction

https://github.com/huzi96/TF-SATD

Progressive Spatial Recurrent Neural Network for Intra Prediction

https://github.com/hyf015/gaze_prediction

Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition

https://github.com/hz-ants/obtain-an-object-mesh-and-create-labels

Real-Time Seamless Single Shot 6D Object Pose Prediction

https://github.com/hz-ants/yolo-6d

Real-Time Seamless Single Shot 6D Object Pose Prediction

https://github.com/ibaiGorordo/ONNX-LSTR-Lane-Detection

End-to-end Lane Shape Prediction with Transformers

https://github.com/ibm/materials

MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network

https://github.com/iesl/geometric_graph_embedding

Complex Embeddings for Simple Link Prediction

https://github.com/iinemo/lm-polygraph

Uncertainty Estimation in Autoregressive Structured Prediction

https://github.com/iitmcvg/CNN_SLAM

CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction

https://github.com/imatge-upc/saliency-2019-SalBCE

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

https://github.com/imatge-upc/saliency-salgan-2017

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

https://github.com/imvishvaraj/ctr_nlp

Deep Interest Network for Click-Through Rate Prediction

https://github.com/inhwanbae/eigentrajectory

Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction

https://github.com/intel-isl/MiDaS

Vision Transformers for Dense Prediction

https://github.com/inyong37/Vision

Deeper Depth Prediction with Fully Convolutional Residual Networks

https://github.com/ip200/venn-abers

Venn-Abers predictors

https://github.com/ipd-tools/ipd

PPI++: Efficient Prediction-Powered Inference

https://github.com/irfanicmll/torchdistiller

Channel-wise Knowledge Distillation for Dense Prediction

https://github.com/irgroup/clef2023-longeval-irc

Document Expansion by Query Prediction

https://github.com/isl-org/MiDaS

Vision Transformers for Dense Prediction

https://github.com/islab-sophia/odisal

DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling

https://github.com/istaustria-cvml/flea

Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction

https://github.com/ivan-chai/hotpp-benchmark

Non-Autoregressive Diffusion-based Temporal Point Processes for Continuous-Time Long-Term Event Prediction

https://github.com/j3xugit/RaptorX-Contact

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

https://github.com/jaemuzzin/plagnn

Inductive Relation Prediction by Subgraph Reasoning

https://github.com/jahaniam/semidepth

Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network

https://github.com/james20141606/eMaize

Applying Machine Learning To Maize Traits Prediction

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