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Ciao, it's Daniele here! πŸ–πŸ»

Solo projects πŸ”₯

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

Group projects πŸš€

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

My study material πŸ‘¨β€πŸŽ“

Daniele Solombrino's Projects

africa-wildlife icon africa-wildlife

Interactive simulation of climate change effects on African wild fauna

aml-2023-24 icon aml-2023-24

Study materials for the "Advanced Machine Learning" exam, Sapienza University of Rome, Prof. Fabio Galasso (A.Y. 2023/24)

biscuits icon biscuits

A set of experiments inspired by the paper "Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs" by Jonathan Frankle, David J. Schwab, Ari S. Morcos

creactive icon creactive

A set of experiments on Deep Neural Networks activation functions

dlai-2022-23 icon dlai-2022-23

Study materials for Deep Learning and Applied AI exam, Sapienza University of Rome, Prof. Emanuele RodolΓ  (A.Y. 2022/23)

fds-2022-23 icon fds-2022-23

Study materials for Fundamentals of Data Science exam, Sapienza University of Rome, Prof. Fabio Galasso (A.Y. 2022/23)

gphungarian icon gphungarian

A GPU-accelerated implementation of the Hungarian Algorithm, written in CUDA

nlp-2022-23 icon nlp-2022-23

Study materials for Natural Language Process exam, Sapienza University of Rome, Prof. Iacopo Masi and Stefano Faralli (A.Y. 2022/23)

nummethcs-2022-23 icon nummethcs-2022-23

Study materials for Numerical Methods for Computer Science exam, Sapienza University of Rome, Prof. Emanuele RodolΓ  (A.Y. 2022/23)

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