Tian0426 / CL-HAR
☆60Updated 2 years ago
Alternatives and similar repositories for CL-HAR:
Users that are interested in CL-HAR are comparing it to the libraries listed below
- Code for our AAAI-2021 paper "Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition".☆37Updated 3 years ago
- Implementation of Contrastive Predictive Coding for Human Activity Recognition☆28Updated 2 years ago
- Official implementation of SWL-Adapt.☆14Updated last year
- Contrastive Learning (SimCLR) for Human Activity Recognition☆75Updated 3 years ago
- COCOA: Cross Modality Contrastive Learning for Sensor Data☆25Updated 2 years ago
- ☆14Updated 2 years ago
- The official implementation of paper "Towards a Dynamic Framework for Multi-Sensor-Based Wearable Human Activity Recognition". Accepted b…☆23Updated 2 years ago
- Contrastive Adversarial Learning for Multi-Source Time Series Domain Adaptation☆27Updated 3 years ago
- Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors☆23Updated 4 years ago
- Contrastive Learning for Domain Adaptation of Time Series☆87Updated 11 months ago
- ☆8Updated 6 years ago
- (WSDM'24) Cross-modal Self-Supervised Learning for Time-series through Latent Masking☆18Updated last year
- Domain Adaptation for Time Series Under Feature and Label Shifts☆117Updated last year
- Improving Human Activity Recognition through Self-training with Unlabeled Data☆40Updated 3 years ago
- The layer-wise training convolutional neural networks using local loss for sensor based human activity recognition☆20Updated 4 years ago
- [TAI 2023] Contrastive Domain Adaptation for Time-Series via Temporal Mixup☆30Updated 11 months ago
- ☆11Updated 2 years ago
- ☆37Updated last year
- Semi-Supervised End-to-End Contrastive Learning for Time Series Classification☆26Updated last year
- Source code for paper: UniTS: Short-Time Fourier Inspired Neural Networks for Sensory Time Series Classification☆19Updated 3 years ago
- The repository provides code implementations and illustrative examples of NeurIPS 2023 paper, Finding Order in Chaos: A Novel Data Augmen…