Pinned Repositories
CroSSL
(WSDM'24) Cross-modal Self-Supervised Learning for Time-series through Latent Masking
data-centric-federated-learning
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
kaizen
(WACV'24) Kaizen: Practical self-supervised continual learning with continual fine-tuning
olp-gnn
papagei-foundation-model
(ICLR'25) PaPaGei: Open Foundation Models for Optical Physiological Signals
proof-as-a-service
salted-dnns
(HotMobile'24) Salted Inference: Enhancing Privacy while Maintaining Efficiency of Split Inference in Mobile Computing
SSLfairness
(KDD’24) Using Self-Supervised Learning Can Improve Model Fairness.
tee-duet
zkstream
Repository for the artifact accompanying our paper "zkStream: a Framework for Trustworthy Stream Processing".
Nokia Bell Labs's Repositories
Nokia-Bell-Labs/papagei-foundation-model
(ICLR'25) PaPaGei: Open Foundation Models for Optical Physiological Signals
Nokia-Bell-Labs/CroSSL
(WSDM'24) Cross-modal Self-Supervised Learning for Time-series through Latent Masking
Nokia-Bell-Labs/salted-dnns
(HotMobile'24) Salted Inference: Enhancing Privacy while Maintaining Efficiency of Split Inference in Mobile Computing
Nokia-Bell-Labs/data-centric-federated-learning
Enhancing Efficiency in Multidevice Federated Learning through Data Selection
Nokia-Bell-Labs/kaizen
(WACV'24) Kaizen: Practical self-supervised continual learning with continual fine-tuning
Nokia-Bell-Labs/SSLfairness
(KDD’24) Using Self-Supervised Learning Can Improve Model Fairness.
Nokia-Bell-Labs/olp-gnn
Nokia-Bell-Labs/pretrained-imu-encoders
Official Repo for PRIMUS: Pretraining IMU Encoders with Multimodal Self-Supervision
Nokia-Bell-Labs/zkstream
Repository for the artifact accompanying our paper "zkStream: a Framework for Trustworthy Stream Processing".
Nokia-Bell-Labs/data-channel-extension
[NeurIPS'24] DEX: Data Channel Extension for Efficient CNN Inference on Tiny AI Accelerators
Nokia-Bell-Labs/proof-as-a-service
Nokia-Bell-Labs/tee-duet
Nokia-Bell-Labs/audio-class-discovery
Nokia-Bell-Labs/MASA_tools_for_IVAS