| Name | Description |
|---|---|
| Biscuits | Achieved 75% of original validation accuracy using just 1% of the parameters, inspired by Training BatchNorm and Only BatchNorm |
| CreActive | Devised techniques to observe statistics, patterns and behaviors of Deep Neural Networks activations |
| GPHungarian | 800x speedup via custom, CUDA-accelerated version of the Hungarian Algorithm |
| Kindergarten-VQ-VAE | Devised custom disentanglement modules for Transformers |
| Name | Description |
|---|---|
| AML_Homework | Devised novel, custom Spatio-Temporal Graph Attention Transformers and CNNs for 3D human pose estimation |
| Big Data FC | Devised novel representations for football teams starting from single players, custom Machine Learning algorithms to predict their end-of-the-season ranking, and a scraper for seasons 2007 to 2012 |
| Braver Cat | Reduced train time by over 60% using Transfer Learning in medical image segmentation |
| Cheap Clasp | Devised custom algorithms to use JPEG image encoder as an alternative to CLIP-like Neural image encoders |
| Distillo, Ergo Sum | Improved student model performances by 10% while using only 10% of its parameters using heterogeneous teacher-student framework (knowledge distillation) on medical images segmentation |
| GeNNuS | Achieved 87% validation accuracy on a music genre classification task and solved vanishing gradient issues |