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Temporal Sequences

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보존된 평가 기록: 1

This task asks models to answer questions about which times certain events could have occurred.

Source: BIG-bench

Image source: BIG-bench

코드

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

https://github.com/D-ST-Sword/ATD

공식 코드

Alternative Telescopic Displacement: An Efficient Multimodal Alignment Method

https://github.com/INK-USC/RE-Net

공식 코드

Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs

https://github.com/IST-DASLab/ScalableMNN

공식 코드

Scalable Mechanistic Neural Networks for Differential Equations and Machine Learning

https://github.com/TrumanPhd/f5C-finder

공식 코드

F5C-finder: An Explainable and Ensemble Biological Language Model for Predicting 5-Formylcytidine Modifications on mRNA

https://github.com/VSainteuf/utae-paps

공식 코드

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks

https://github.com/WeihengZ/Explainable-Graph-Autoformer

공식 코드

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting

https://github.com/aneesperingal/rul-prediction

공식 코드

Remaining Useful Life Prediction for Aircraft Engines using LSTM

https://github.com/chenguolin/nutime

공식 코드

NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining

https://github.com/chenkang455/s-sdm

공식 코드

SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams

https://github.com/chenyizi086/wu.2023.sigspatial

공식 코드

Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps

https://github.com/christopher-irw/proformer_ce

공식 코드

Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring

https://github.com/cruiseresearchgroup/AuxMobLCast

공식 코드

Leveraging Language Foundation Models for Human Mobility Forecasting

https://github.com/ejcorn/brain_states

공식 코드

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands

https://github.com/enesavc/subreg_deeplearning

공식 코드

Subregular Complexity and Deep Learning

https://github.com/ermongroup/teochat

공식 코드

TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data

https://github.com/fabro66/GAST-Net-3DPoseEstimation

공식 코드

A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video

https://github.com/februarysea/trajscenellm

공식 코드

TrajSceneLLM: A Multimodal Perspective on Semantic GPS Trajectory Analysis

https://github.com/fekoester/AERes

공식 코드

Attention-Enhanced Reservoir Computing

https://github.com/galatolofederico/icpram2019

공식 코드

Using stigmergy as a computational memory in the design of recurrent neural networks

https://github.com/gcampede/terrorism-metagraphs

공식 코드

Learning future terrorist targets through temporal meta-graphs

https://github.com/gebob19/m2a

공식 코드

M2A: Motion Aware Attention for Accurate Video Action Recognition

https://github.com/graph-machine-learning-group/sgp

공식 코드

Scalable Spatiotemporal Graph Neural Networks

https://github.com/hadjisma/VideoAlignment

공식 코드

Representation Learning via Global Temporal Alignment and Cycle-Consistency

https://github.com/hzc1208/ANN2SNN_SRP

공식 코드

Reducing ANN-SNN Conversion Error through Residual Membrane Potential

https://github.com/issaccv/KAN-AD

공식 코드

KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks

https://github.com/jiapingz/shapeDTW

공식 코드

shapeDTW: shape Dynamic Time Warping

https://github.com/jingjing-unilu/pca_transformer

공식 코드

Transformer Multivariate Forecasting: Less is More?

https://github.com/jonashuegel/tspmplus_r

공식 코드

tSPM+; a high-performance algorithm for mining transitive sequential patterns from clinical data

https://github.com/jonashuegel/tspmplusdocker

공식 코드

tSPM+; a high-performance algorithm for mining transitive sequential patterns from clinical data

https://github.com/luileito/handwriting-biometrics

공식 코드

Human or Machine? It Is Not What You Write, But How You Write It

https://github.com/lukashedegaard/continual-skeletons

공식 코드

Continual Spatio-Temporal Graph Convolutional Networks

https://github.com/maithili/spatiotemporalobjecttracking

공식 코드

Proactive Robot Assistance via Spatio-Temporal Object Modeling

https://github.com/mauricekraus/xlstm-mixer

공식 코드

xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories

https://github.com/mililab/timo

공식 코드

TiMo: Spatiotemporal Foundation Model for Satellite Image Time Series

https://github.com/mlgig/amee

공식 코드

Robust Explainer Recommendation for Time Series Classification

https://github.com/neuroai-workshop-anon-1224113/working-memory-facilitating-reservoir-learning

공식 코드

Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks

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