Name: Aristotelis-Angelos Papadopoulos
Type: User
Company: University of Southern California (USC)
Bio: PhD student at USC. Interested in Machine Learning, Deep Learning and Optimization.
Location: Los Angeles
Blog: https://www.linkedin.com/in/aristotelisangelospapadopoulos6b25a8113/
Aristotelis-Angelos Papadopoulos's Projects
Code for "High-Precision Model-Agnostic Explanations" paper
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
A curated list of awesome anomaly detection resources
A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition
Deep Learning Specialization by Andrew Ng on Coursera.
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
Used NLP to extract important features from Reddit News and combined those features with Random Forest and Boosting algorithms to predict the DJIA market index movement.
Designed an Image Segmentation (SegNet) model and a Graph Convolutional Neural Network and applied them on a financial graph database provided by Bloomberg.
Human Activity Recognition using Time Series Classification
Built a Neural Network in Keras that beat the Top Voted Kaggle kernel and explained its predictions using Rules and the package "Anchors" proposed in the paper High Precision Model-Agnostic Explanations published in AAAI in 2018.
Implemented Gradient Descent, Newton, Modified Newton, DFP and BFGS numerical optimization algorithms in C from scratch and compared the results with the commercial AMPL'S MINOS solver.
Fine-tuned BERT on SQuAd 2.0 Dataset. Applied Knowledge Distillation (KD) and fine-tuned DistilBERT (student) using BERT as the teacher model. Reduced the size of the original BERT by 40%.
Tensorflow implementations of Relational Networks and a VQA dataset named Sort-of-CLEVR proposed by DeepMind.
A unified approach to explain the output of any machine learning model.
A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).