-
UvA Language Technology Lab @ltl-uva
- Amsterdam
- https://vene.ro
- @vnfrombucharest
Stars
𝗢𝘄𝗻 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲. Skore's open-source Python library accelerates ML model development with automated evaluation reports, smart methodological guidance, and comprehensive cross-validation analy…
A word2vec negative sampling implementation with correct CBOW update.
Teaching tool and debugging aid in context of references, mutable data types, and shallow and deep copy.
Implementing Bert to improve word2gauss model
Repository for thesis project about efficient localization for sparsemax on GPU (will change repository name later)
Bicleaner is a parallel corpus classifier/cleaner that aims at detecting noisy sentence pairs in a parallel corpus.
NLQuAD: A Non-Factoid Long Question Answering Data Set. To be published at EACL2021
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
Stochastic Automatic Differentiation library for PyTorch.
Implementation of Sparsemax activation in Pytorch
Open-Source Machine Translation Quality Estimation in PyTorch
A simple guide (and example of configuration) about how to install i3 & its and essentials packages, then make them look eye candy, also contains my dotfiles of Debian 12 (Bookworm) setup
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
A highly efficient implementation of Gaussian Processes in PyTorch
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
A neural network architecture for NLP tasks, using cython for fast performance. Currently, it can perform POS tagging, SRL and dependency parsing.
A PyTorch implementation of a Factorization Machine module in cython.
A frame-semantic parsing system based on a softmax-margin SegRNN.
A neural TurboSemanticParser as described in "Deep Multitask Learning for Semantic Dependency Parsing", Peng et al., ACL 2017.
Minimal and Clean Reinforcement Learning Examples
Stochastic Neighbor and Crowd Kernel (SNaCK) embeddings: Quick and dirty visualization of large-scale datasets via concept embeddings