Search Results for author:
Found 9 papers, 3 papers with code
Towards human-level performance on automatic pose estimation of infant spontaneous movements
Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants.
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles
The ensembled prediction intervals are aggregated as a split normal mixture accounting for possible multimodality and asymmetricity of the posterior predictive distribution, and resulting in prediction intervals that capture aleatoric and epistemic uncertainty.
EfficientPose: Scalable single-person pose estimation
Single-person human pose estimation facilitates markerless movement analysis in sports, as well as in clinical applications.
Ranked #3 on
Pose Estimation
on MPII Single Person
Forecasting Intra-Hour Imbalances in Electric Power Systems
Keeping the electricity production in balance with the actual demand is becoming a difficult and expensive task in spite of an involvement of experienced human operators.
Securing Tag-based recommender systems against profile injection attacks: A comparative study. (Extended Report)
This work addresses the challenges related to attacks on collaborative tagging systems, which often comes in a form of malicious annotations or profile injection attacks.
Extracting News Events from Microblogs
As part of the evaluation, we compare our approach with a related state-of-the-art solution.
Context-Aware Sequence-to-Sequence Models for Conversational Systems
This work proposes a novel approach based on sequence-to-sequence (seq2seq) models for context-aware conversational systems.
Detecting Offensive Language in Tweets Using Deep Learning
This paper addresses the important problem of discerning hateful content in social media.
A Deep Network Model for Paraphrase Detection in Short Text Messages
Our experimental results show that the proposed approach outperforms existing state-of-the-art approaches on user-generated noisy social media data, such as Twitter texts, and achieves highly competitive performance on a cleaner corpus.
