About
Blog
Pills
Software
Trainings
Seminar
⚲
Search results
Our blog
We publish
introductory posts
for beginners and
paper digests
for experienced people on a tight schedule.
All posts
Applications of data valuation in machine learning
At TransferLab we have extensively covered existing and developing methods for Data valuation, the task of attributing value to samples in a …
FLAME 2023: Diving into the Future of Fluid Dynamics and Machine Learning
At the Stanford FLAME AI Workshop 2023, I immersed myself in the intersection of machine learning and fluid dynamics, benefiting from …
AutoDev: Exploring Custom LLM-Based Coding Assistance Functions
We explore the potential of custom code assistant functions based on large language models (LLMs). With our open-source software package …
Our take on IJCAI 2022
The International Joint Conference on Artificial Intelligence (IJCAI) is a premier event for researchers working in all areas of AI.
The hidden assumptions and pitfalls of density based anomaly detection
Anomaly detection is a notoriously ill-defined problem. The notion of an anomaly is arguably subjective since it depends to some extent on …
Our take on ICLR 2022 - Part 2
ICLR is one of the most important and prestigious conferences in the ML community. It spans all ML topics, from embeddings to Graph neural …
Our take on ICLR 2022 - Part 1
ICLR is one of the most important and prestigious conferences in the ML community. It spans all ML topics, from embeddings to Graph neural …
Certified error rates for neural networks
Adversarial training has been shown to improve robustness of neural networks to certain classes of data perturbations. Despite constant …
Natural, Trust Region and Proximal Policy Optimization
We present an overview of the theory behind three popular and related algorithms for gradient based policy optimization: natural policy …
Cross-validation: what does it estimate?
In Cross-validation: what does it estimate and how well does it do it? Bates et al. focus on cross validation for error estimation and show …
Calibration of Classifiers
We discuss the calibration of probabilistic classifiers, i.e. the question of whether the output vectors of such classifiers accurately …
Solving PDEs With Neural Networks
We discuss some current trends in applying ML to the solution of differential equations, and the difficulties faced. We focus on a family of …
