Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings

Deep Multimodal Guidance for Medical Image Classification: https://arxiv.org/pdf/2203.05683.pdf

We use reinforcement learning to study how language can be used as a tool for agents to accomplish tasks in their environment, and show that structure in the evolved language emerges naturally through iterated learning, leading to the development of compositional language for describing and generalising about unseen objects.

Predicting the multi-trajectory evolution of multimodal brain connectivity.

This project creates the T4SA 2.0 dataset, i.e. a big set of data to train visual models for Sentiment Analysis in the Twitter domain using a cross-modal student-teacher approach.

Source code for "Few-Shot Transfer Learning for Hereditary Retinal Diseases Recognition" (MICCAI 2021)

Implementation of Adversarial Training for BERT and BERT-Like Models and Analysis of effects of model compression on Robustness of a model

Detection of cerebral microbleeds using deep learning method consisting of 2 steps: initial candidate detection and candidate discrimination using a student-teacher network.

Knowledge distillation for masked FER using ResNet-18 in PyTorch.

This is an implementation for paper Automated training of location-specific edge models for traffic counting