Retrieval-Augmented Diffusion Models for Time Series Forecasting
NeurIPS 2024
Time Series (Paper)
MixLinear; Extereme Low Resource Multivaraite Time Series Forecasting with 0.1K Parameters
Arxiv 2024
MambaTS; Improved Selective SSM for LTSF
arxiv 2024
VCformer; Variable Correlation Transformer with Inherent Lagged Correlation for MTS Forecasting
arxiv 2024
(발표 자료) MAMBA
(발표 자료) Selective SSM: MAMBA
(발표 자료) BRL; Time Series Diffusion Models 2
(발표 자료) BRL: Time Series Diffusion Models 2
(발표 자료) BRL; Time Series Diffusion Models
(발표 자료) BRL: Time Series Diffusion Models 1
TimesURL; Self-supervised Contrastive Learning for Universal Time Series Representation Learning
AAAI 2024
Self-supervised Contrastive Forecasting
ICLR 2024
Masked Diffusion Models are Fast Distribution Learners
ICLR 2024 (?)
DiffLoad; Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model
arXiv 2023
Distribution Shift
arXiv 2023
Consistency Models
arxiv 2023
Lag-Llama; Towards Foundation Models for Time Series Forecasting
Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models at NeurIPS 2023
TimeGPT-1
arxiv 2023
All About Score-based Models
All About Score-based Models
Regular Time-series Generation using SGM
arxiv 2023
All About Diffusion
All About Diffusion Models
FITS; Modeling TS with 10k Parameters
ICLR 2024 (?)
(발표 자료) Channel Identification in Time Series
연세대학교 기초연구실 발표자료
Predict, Refine, Synthesize; Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
NeurIPS 2023
FilterAugment; An Acoustic Environmental Data Augmentation Method
Interspeech 2022
SpecAugment++; A Hidden Space Data Augmentation Method for Acoustic Scene Classification
Interspeech 2021
(발표 자료) Time Series Foundation Model
연세대학교 기초연구실 발표자료
SpecAugment on Large Scale Datasets
ICASSP 2019
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
Interspeech 2023
MAE-AST; Masked Autoencoding Audio Spectogram Transformer
Interspeech 2022
Score-based Generative Modeling by Diffusion Process
Score-based Generative Modeling by Diffusion Process
Audio Self-supervised Learning; A Survey
arxiv 2022
Masked Autoencoders that Listen
NeurIPS 2022
Unsupervised feature learning for audio classification using convolutional deep belief networks
NeurIPS 2009
AST; Audio Spectrogram Transformer
arxiv 2021
Speaker Recognition from Raw Waveform with SincNet
IEEE Spoken Language Technology Workshop 2018
(paper 102) DCdetector; Dual Attention Contrastive Representation Learning for TS Anomaly Detection
KDD 2023
(paper 100) Non-stationary Transformers:Exploring the Stationarity in Time Series Forecasting
NeurIPS 2022
(paper 97) Dish-TS; A General Paradigim for Alleviating Distribution for Time Series Forecasting
AAAI 2023
(발표 자료) TSMixer
(발표 자료) TSMixer
CRPS (Continuous Ranked Probability Score)
CRPS (Continuous Ranked Probability Score)
(발표 자료) Beit; Bert pre-training of image transformers
(발표 자료) SSL with TS data
(발표 자료) MIM, CL
(발표 자료) MIM, CL
(발표 자료) SSL with TS data 3
연세대학교 기초연구실 발표자료
(paper) CAN; A Simple, Efficient and Scalable CMAE framework for learning Visual Representations
2023
(발표 자료) SSL with TS data
연세대학교 기초연구실 발표자료
(paper) REST
2022
(발표 자료) T-Loss with MTS, TNC
연세대학교 기초연구실 발표자료
(paper 66) SemiTime
2021
(paper 65) SeqCLR
2020
(paper 61) CA-TCC
2022
(code) Temporal Neighborhood Coding (TNC)
Temporal Neighborhood Coding (TNC)
(paper 58) CaSS
2022
(code) Causal CNN
Causal CNN
(code) Triplet Loss for Time Series
Triplet Loss for Time Series
(paper 55) TF-C
2022
(paper 54) Self-Supervised TS Representation Learning with Temporal-Instance Similarity Distillation
2022
(paper 53) Self-Time
2021
(paper 33) TS2Vec
2022
(paper 32) TS-TCC
2021
(paper) Neural Relational Inference for Interacting Systems
Graph Neural Network (2018)
(paper) Balanced Graph Structure Learning for MTS Forecasting
Graph Neural Network (2022)
(paper) A Study of Joint Graph Inference and Forecasting
Graph Neural Network (2021)
GraphWavenet 코드 리뷰
pytorch, pytorch geometric
StemGNN 코드 리뷰
pytorch, pytorch geometric
LSTNet 코드 리뷰
pytorch, pytorch geometric
MTAD-GAT 코드 리뷰
pytorch, pytorch geometric
MTGNN 코드 리뷰
pytorch, pytorch geometric
GDN 코드 리뷰
pytorch, pytorch geometric
(PyG) Pytorch Geometric Temporal
pytorch geometric temporal
(paper) Predictive Temporal Embedding of Dynamic Graphs
Graph Neural Network (2020)
(paper) Transfer GNN for pandemic forecasting
Graph Neural Network (2021)
(paper) GMAN ; A Graph Multi-Attention Network for Traffic Prediction
Graph Neural Network (2019)
(paper) Multi-scale temporal feature extraction based GCN with Attention for MTS Prediction
Graph Neural Network (2022)
(paper) Predicting Path Failure in Time-Evolving Graphs
Graph Neural Network (2019)
(paper) MTS forecasting with Latent Graph Inference
Graph Neural Network (2021)
(paper) GC-LSTM ; GCN embedded LSTM for Dynamic Network Link Prediction
Graph Neural Network (2018)
(paper) MTHetGNN ; A Heterogeneous Graph Embedding Framework for MTS forecasting
Graph Neural Network (2020)
(paper) Structued Sequence Modeling with GCRN (2016)
Graph Neural Network (2016)
(paper) MAGNN ( Multi-Scale Adaptive GNN ) for MTS Forecasting
Graph Neural Network (2022)
(paper) Two-Stream(2s) AGCN for Skeleton-Based Action Recognition (2019)
Graph Neural Network (2019)
(paper) ASTGCN ; Attention Based Spatial-Temporal GCN for Traffic Flow Forecasting
Graph Neural Network (2019)
(paper) Adaptive GCRN for Traffic Forecasting
Graph Neural Network (2020)
(paper) A3T-GCN ; Attention Temporal GCN for Traffic Forecasting
Graph Neural Network (2020)
(paper) T-GCN ; A Temporal GCN for Traffic Prediction
Graph Neural Network (2015)
(paper) SSDNet ; State Space Decomposition NN for TS Forecasting
Time Series Forecasting (2021)
(paper) Pyraformer ; Low-Complexity Pyramidal Attention for Long-Rang TS modeling and forecasting
Time Series Forecasting (2022)
(paper) FEDformer ; Frequency Enhanced Decomposed Transformer for Long-term TS Forecasting
Time Series Forecasting (2022)
(paper) STCGAT ; Spatial-temporal Causal Networks for complex urban road traffic flow prediction
Time Series Forecasting, GNN (2022)
(paper) Learning Graph Structures with Transformer for MTS Anomaly Detection in IoT
Time Series Anomaly Detection, GNN (2022)
(paper) Mixing Up Contrastive Learning ; Self-Supervised Representation Learning for TS
Time Series Representation, Contrastive Learning (2022)
(paper) SAITS ; Self-Attention-based Imputation for TS
Time Series Imputation (2022)
(paper) Robust Probabilistic Time Series Forecasting
Probabilistic Forecast (2022)
(paper) Transformers in Time Series ; A Survey
Transformer (2022)
(paper) Graph Augmented Normalizing Flows for AD of MTS
GNN, AD, NF (2022)
(paper) Deep Gate ; Global-local decomposition for MTS modeling
Time Series Decomposition, Forecasting (2022)
(paper) Multivariate Time Series Anomaly Detection via Graph Attention Network
Anomaly Detection with GNN (2020, 44)
(paper) Multivariate Time Series Regression with Graph Neural Networks
Time Series Forecasting with GNN (2022)
(paper) Representation Learning via Invariant Causal Mechanisms
Representation Learning (2020, 47)
(paper) COST ; Contrastive Learning of Disentangled Seasonal-Trend Representations for TS forecasting
Representation Learning (2022)
(paper) Unsupervised Representation Learning for TS with Temporal Neighborhood Coding
Representation Learning (2021, 14)
(paper) Connecting the Dots ; MTS Forecasting with GNNs
Time Series Forecasting (2020, 147)
(paper) Multivariate Time Series Forecasting with Transfer Entropy Graph
Time Series Forecasting (2020, 5)
(paper) Think Globally, Act Locally ; A DNN approach to High-Dimensional TSF
Time Series Forecasting (2019,120)
(paper) TCN for Anomaly Detection in TS
Time Series Anomaly Detection (2019,34)
(paper) Deep State Space Models for TS Forecasting
Time Series Forecasting (2018,266)
(paper) Neural Decomposition of TD data for Effective Generalization
Time Series Decomposition (2017,40)
(paper) Graph WaveNet for Deep Spatial-Temporal Graph Modeling
GNN, Graph WaveNet, Time Series Forecasting (2019,337)
(paper) Diffusion Convolutional Recurrent Neural Network ; Data-driven Traffic Forecasting
GNN, DCRNN, Time Series Forecasting (2017,1122)
(paper) A Memory Network Based Solution for MTS Forecasting
Time Series Forecasting (2018,42)
DeepHit
Survival Analysis
생존 분석 (Survival Analysis) 기초
Survival Analysis, Kaplan-Meier, RNN-Surv
(code) Global, Local, Global & Local
Global, Local, Global & Local
(code) DTW inverse sample
DTW inverse sample
(paper) 계절조정을 활용한 전이학습 기반의 자동차 예비 부품 장기수요 예측
고려대학교 산공과 & 현대자동차
(paper) GNN-based Anomaly Detection in MTS
GNN for Anomaly Detection (2021, 32)
(paper) Spectral Temporal GNN for MTS Forecasting
GNN for TSF (2021, 41)
(paper) METRO ; A Generic GNN Framework for MTS Forecasting
GNN for TSF (2020, 131)
(paper) Discrete Graph Structure Learning for Forecasting Multiple Time Series
GNN for TSF (2021, 11)
(paper) Learning Discrete Structures for GNNs
Learning Discrete Structures for GNNs (2019, 145)
(paper) Domain Adaptation for TSF via Attention Sharing
Transfer Learning in Time Series Forecasting (2021)
(paper) DATSING ; Data Augmented Time Series Forecasting with Adversarial Domain Adaptation
Transfer Learning in Time Series Forecasting (2020, 1)
(paper) If you like it, GAN it ; Probabilistic MTS Forecast with GAN
Time Series Forecasting (2020, 9)
(paper) Deep and Confident Prediction for Time Series at Uber
Time Series Forecasting (2017, 270)
(paper) Conditional Time Series Forecasting with CNN
Time Series Forecasting (2017, 303)
(paper) Temporal Pattern Attention for Multivariate Time Series Forecasting
Time Series Forecasting (2018, 164)
(paper) Modeling Long and Short Term Temporal Patterns with DNN
Time Series Forecasting (2017, 496)
(paper) Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Time Series Forecasting (2019, 193)
(paper) Deep Transformer Models for Time Series Forecasting ; The Influenza Prevalence Case
Time Series Forecasting (2020, 97)
(paper) Probabilistic Forecasting of Sensory Data with GAN ; ForGAN
Time Series Forecasting (2019, 32)
(paper) Forecasting with Time Series Imaging
Time Series Forecasting (2019, 21)
(paper) Deep Adaptive Input Normalization for Time Series Forecasting
Time Series Forecasting (2019, 25)
(paper) Time Series is a Special Sequence ; Forecasting with Sample Convolution and Interaction
Time Series Forecasting (2021)
(paper) Deep Learning For Time Series Classification
Time Series Classification (2018, 1191)
(paper) Recurrent Neural Networks for MTS with Missing Values
Time Series Imputation (2018, 1114)
(paper) Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation
Change Point Detection (2020, 4)
(paper) Change Point Detection in Time Series Data by Relative Density Ratio Estimation
Change Point Detection (2012, 440)
(paper) Adjusting for Autocorrelated Errors in Neural Networks for Time Series
Time Series Regression (2021)
(paper) Adversarial Examples in Deep Learning for Multivariate Time Series Regression
Time Series Regression (2020,9)
(paper) A Multi-Horizon Quantile Recurrent Forecaster
Time Series Regression (2017, 137)
(paper) A Transformer-based Framework for Multivariate Time Series Representation Learning
Time Series Regression (2020,22)
(paper) Unsupervised Scalable Representation Learning for Multivariate Time Series
2019, Triplet Loss
(paper) Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks (ForGAN)
2019, ForGAN
(paper) Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity
2020, STRIPE
(paper) Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
2020, TFT
(paper) Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
2020, LogSparseTransformer
(paper) Deep MTS Embedding Clustering via Attentive-Gated Autoencoder
2020, Time Series Clustering
(paper) Clustering Time Series Data through Autoencoder-based Deep Learning Models
2020, Time Series Clustering
(paper) Learning Representations for Time Series Clustering
2019, Time Series Clustering
[code review] NBeats
NBEATS, pytorch
(paper) A benchmark study on time series clustering
2020, TS clustering
[code review] Informer
Informer, pytorch
(paper) Time-series Generative Adversarial Networks
2019, TimeGAN
(paper) End-to-end Multi-task Learning of Missing Value Imputation and Forecasting in Time-Series Data
2021, Multi-task, Imputation & Forecasting
(paper) Dilated Recurrent Neural Networks
2017, Dilated RNN
(paper) Multi-Task Time Series Forecasting with Shared Attention
2021, MTL-Trans, Multi-task Learning, Shared-Private Attention Sharing
(paper) Multi-step Forecasting via Multi-task Learning
2019, Multi-task Learning
(paper) Challenges and Approaches to Time-Series Forecasting in DT Center Telemetry ; A Survey
2021, survey2
(paper) Neural Basis Expansion analysis with exogenous variables ; Forecasting electricity prices with NBEATSx
2021, NBEATSx
(paper) N-Beats ; Neural Basis Expansion Analysis for Interpretable Time Series Forecasting
2020, N-Beats
(paper) Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
2021, Conditioned Normalizing Flows
(paper) Time Series is a Special Sequence ; Forecasting with Sample Convolution and Interaction
2021, SCINet
(paper) Informer ; Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
2021,Informer
(paper) A Transformer-based Framework for Multivariate Time Series Representation Learning
2020,Transformer
(paper) Wavenet ; A generative model for raw audio
2016, Wavenet, TCN
[multimodal] Neural FE of signal data - (2) SincNet
Signal Data, Wav2Vec, SincNet, PASE
[multimodal] Neural FE of signal data - (1) Wav2Vec
Signal Data, Wav2Vec, SincNet, PASE
[multimodal] FE of signal data - (2) MFCC
Signal Data, Fourier Transform, MFCC
[multimodal] FE of signal data - (1) Fourier Transform
Signal Data, Fourier Transform, MFCC