RenlyH
Follow
Starred repositories
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
TextGrad: Automatic ''Differentiation'' via Text -- using large language models to backpropagate textual gradients.
Machine Learning and Computer Vision Engineer - Technical Interview Questions
Clinical Histopathology Imaging Evaluation Foundation Model
Large Language-and-Vision Assistant for Biomedicine, built towards multimodal GPT-4 level capabilities.
A toolkit for integrating histology and spatial transcriptomics - NeurIPS 2024
Visual foundation model enabling rapid, accurate detection of brain tumor infiltration during surgery
Using the Great Lakes cluster and batch computing with SLURM
The guide to online assessments and interviews
Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction
TCGA Pathology Reports in Machine Readable Text
ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image Classification (CVPR 2024)
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Multimodal prototyping for cancer survival prediction - ICML 2024
Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images - ICCV 2021
Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024
Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024
Speed up Stable Diffusion with this one simple trick!
A beautiful, simple, clean, and responsive Jekyll theme for academics
[NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
❄️🔥 Visual Prompt Tuning [ECCV 2022] https://arxiv.org/abs/2203.12119
[ICLR 2023 Spotlight] Vision Transformer Adapter for Dense Predictions
Low rank adaptation for Vision Transformer
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Implementation of I-JEPA from "Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture"
Open source tools for computational pathology - Nature BME