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Found 7 papers, 1 papers with code
Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling
For object detection, it is possible to view the prediction of bounding boxes as a reverse diffusion process.
Feature Attribution Explanations for Spiking Neural Networks
We present \textit{Temporal Spike Attribution} (TSA), a local explanation method for SNNs.
How model accuracy and explanation fidelity influence user trust
We also found that users cannot be tricked by high-fidelity explanations into having trust for a bad classifier.
Fast and Discriminative Semantic Embedding
The embedding of words and documents in compact, semantically meaningful vector spaces is a crucial part of modern information systems.
Learning spectro-temporal features with 3D CNNs for speech emotion recognition
In this paper, we propose to use deep 3-dimensional convolutional networks (3D CNNs) in order to address the challenge of modelling spectro-temporal dynamics for speech emotion recognition (SER).
Towards Speech Emotion Recognition "in the wild" using Aggregated Corpora and Deep Multi-Task Learning
In order to improve the generalisation capabilities of the emotion models, we propose to use Multi-Task Learning (MTL) and use gender and naturalness as auxiliary tasks in deep neural networks.
Latent Hierarchical Model for Activity Recognition
The model is embedded with a latent layer that is able to capture a richer class of contextual information in both state-state and observation-state pairs.
