DDU
Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
Possibly Available
About
Head of Technology at Finster AI
Evidence-backed skills
Repositories
ldifs_code
Repository for the paper: Fine-tuning can cripple your foundation model; preserving features may be the solution
Spelling_Correction_N-gram_Models
The repository contains code for automated spelling correction using n-gram models and also uses phonemes for aiding the process. Tests have been carried out on uni, bi, tri and tetra gram models but the 4-gram data has not been uploaded due to its large size.
Time_Series_Structure_Detection
Unsupervised approach for automated structure detection in any given time-series
starter-academic
🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify
CVPR-2023-Papers
CVPR 2023 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. A star in the development of visual intelligence!
FLYP
Code for Finetune like you pretrain: Improved finetuning of zero-shot vision models
uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more