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Prediction

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보존된 평가 기록

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코드

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

https://github.com/erfmah/answering_graph_queries

공식 코드

Deep Generative Models for Subgraph Prediction

https://github.com/erikostrowski/isle

공식 코드

ISLE: A Framework for Image Level Semantic Segmentation Ensemble

https://github.com/erionc/paper-length

공식 코드

How Many Pages? Paper Length Prediction from the Metadata

https://github.com/espnet/espnet

공식 코드

Bayes Risk Transducer: Transducer with Controllable Alignment Prediction

https://github.com/etashguha/sparse_conformal

공식 코드

Conformalization of Sparse Generalized Linear Models

https://github.com/eternityzy/cchmm

공식 코드

Causal conditional hidden Markov model for multimodal traffic prediction

https://github.com/eternityzy/stnscm

공식 코드

Spatio-temporal neural structural causal models for bike flow prediction

https://github.com/ethanhezhao/NARM

공식 코드

Leveraging Node Attributes for Incomplete Relational Data

https://github.com/etienne4/PDLA

공식 코드

The Primal-Dual method for Learning Augmented Algorithms

https://github.com/eusip/POM

공식 코드

A multimodal movie review corpus for fine-grained opinion mining

https://github.com/evan-dong/demographic-prediction-argmax-bias

공식 코드

Addressing Discretization-Induced Bias in Demographic Prediction

https://github.com/evita35/joint-rna-compression

공식 코드

RNA secondary structures: from ab initio prediction to better compression, and back

https://github.com/exisas/lgc-vd

공식 코드

Video Diffusion Models with Local-Global Context Guidance

https://github.com/expertailab/textual-entailment-for-effective-triple-validation-in-object-prediction

공식 코드

Textual Entailment for Effective Triple Validation in Object Prediction

https://github.com/exscientia/abodybuilder3

공식 코드

ABodyBuilder3: Improved and scalable antibody structure predictions

https://github.com/facebookresearch/SEAL_OGB

공식 코드

Link Prediction without Graph Neural Networks

https://github.com/facebookresearch/SlowFast

공식 코드

Masked Feature Prediction for Self-Supervised Visual Pre-Training

https://github.com/facebookresearch/detectron2/tree/master/projects/TensorMask

공식 코드

TensorMask: A Foundation for Dense Object Segmentation

https://github.com/facebookresearch/icp-block-mdp

공식 코드

Invariant Causal Prediction for Block MDPs

https://github.com/facebookresearch/image-to-set

공식 코드

Elucidating image-to-set prediction: An analysis of models, losses and datasets

https://github.com/facebookresearch/jepa

공식 코드

Revisiting Feature Prediction for Learning Visual Representations from Video

https://github.com/facebookresearch/maze_navigation_MLMU

공식 코드

Transformers Can Navigate Mazes With Multi-Step Prediction

https://github.com/facebookresearch/mtm

공식 코드

Masked Trajectory Models for Prediction, Representation, and Control

https://github.com/facebookresearch/phyre-fwd

공식 코드

Forward Prediction for Physical Reasoning

https://github.com/facebookresearch/ppuda

공식 코드

Parameter Prediction for Unseen Deep Architectures

https://github.com/facebookresearch/private_prediction

공식 코드

The Trade-Offs of Private Prediction

https://github.com/facebookresearch/taskmet

공식 코드

TaskMet: Task-Driven Metric Learning for Model Learning

https://github.com/facebookresearch/tkbc

공식 코드

Tensor Decompositions for temporal knowledge base completion

https://github.com/fairydance/deeprli

공식 코드

DeepRLI: A Multi-objective Framework for Universal Protein--Ligand Interaction Prediction

https://github.com/fangchangma/sparse-to-dense

공식 코드

Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image

https://github.com/fanmengwang/mmpolymer

공식 코드

MMPolymer: A Multimodal Multitask Pretraining Framework for Polymer Property Prediction

https://github.com/fantasy-shaw/h-stformer

공식 코드

Transport-Hub-Aware Spatial-Temporal Adaptive Graph Transformer for Traffic Flow Prediction

https://github.com/farbodtaymouri/MLMME

공식 코드

A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences

https://github.com/faresbougourzi/3rd-cov19d-competition

공식 코드

2D and 3D CNN-Based Fusion Approach for COVID-19 Severity Prediction from 3D CT-Scans

https://github.com/fau-is/xnap

공식 코드

XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP

https://github.com/fbargaglistoffi/machine-learning-firm-dynamics

공식 코드

Supervised learning for the prediction of firm dynamics

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