36 citations · 230 across the 39 of their papers we have counts for
7 papers · 1 filter
Limitations in Employing Natural Language Supervision for Sensor-Based Human Activity Recognition -- And Ways to Overcome Them
Harish Haresamudram, Apoorva Beedu, Mashfiqui Rabbi +3
Cross-modal contrastive pre-training between natural language and other modalities, e.g., vision and audio, has demonstrated astonishing performance and effectiveness across a dive…
Towards Learning Discrete Representations via Self-Supervision for Wearables-Based Human Activity Recognition
Harish Haresamudram, Irfan Essa, Thomas Ploetz
Human activity recognition (HAR) in wearable computing is typically based on direct processing of sensor data. Sensor readings are translated into representations, either derived t…
Investigating Enhancements to Contrastive Predictive Coding for Human Activity Recognition
Harish Haresamudram, Irfan Essa, Thomas Ploetz
The dichotomy between the challenging nature of obtaining annotations for activities, and the more straightforward nature of data collection from wearables, has resulted in signifi…
VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement
Erik Wijmans, Irfan Essa, Dhruv Batra
We present Variable Experience Rollout (VER), a technique for efficiently scaling batched on-policy reinforcement learning in heterogenous environments (where different environment…
Learning Temporal Rules from Noisy Timeseries Data
Karan Samel, Zelin Zhao, Binghong Chen +4
Events across a timeline are a common data representation, seen in different temporal modalities. Individual atomic events can occur in a certain temporal ordering to compose highe…
PLAN-B: Predicting Likely Alternative Next Best Sequences for Action Prediction
Dan Scarafoni, Irfan Essa, Thomas Ploetz
Action prediction focuses on anticipating actions before they happen. Recent works leverage probabilistic approaches to describe future uncertainties and sample future actions. How…
Contrastive Predictive Coding for Human Activity Recognition
Harish Haresamudram, Irfan Essa, Thomas Ploetz
Feature extraction is crucial for human activity recognition (HAR) using body-worn movement sensors. Recently, learned representations have been used successfully, offering promisi…