Center for Data Science

Nyhetsarkiv for Center for Data Science

What I currently think about machine learning in health, is that it will lead to better health in the world I will try to touch several issues, using examples from the literature and mine (this will be mainly breast cancer models for personalized therapy), among which bias, intelligence (the dynamic one and the hard-coded one), explain black box models (or stop using them?) and slow-AI.
Iain George Johnston will talk about HyperTraPS (hypercubic transition path sampling), a highly generalisable Bayesian approach which efficiently learns evolutionary and progression pathways from cross-sectional, longitudinal, or phylogenetically linked data.
The speaker will focus on the following topics: inferring topological invariants of latent structures from data, enriching dimension reduction layouts, and modeling human perception to design more trustworthy Machine Learning techniques.
With the advances in image editing and image synthetizing techniques, a new phrase well describes the reality: “Seeing is disbelieving”. Duc Tien Dang Nguyen and his team are working to restore truth in visual media.
The focus of this seminar will be on trajectory inference methods, a novel class of unsupervised computational techniques to model dynamic processes.
In this talk, the speaker will introduce an approach to dealing with simulator imperfection from a point of view of functional approximation that can be implemented through a certain machine learning method, such as kernel-based learning.
The talk will give an overview of computational methods for protein structure prediction.
A seminar about how distant reading and network analysis can be used to develop a big picture of cultural discourse about machine vision technologies.
The objective of the workshop is to build bridges between parameterized complexity theory and practical applications.
Data science relatert seminar på maskinlæring og visual analytics (foredragsholder: Chaoran Fan).
Dette seminaret arrangeres for å fremme samarbeidet mellom NORA (Norwegian Artificial Intelligence Research Consortium) og UiB sine forskere som jobber på kunstig intelligens og maskinlæring.
This meeting is focused on kernelization, the rigorous theory of preprocessing.
On Friday the 5th of April at 10am Jürgen Bernard will give a talk at the Visual Computing Forum. The talk will take place at Lille Aud. @ Høyteknologisenteret (Thormøhlens gate 55). The title of the talk is: Enhancing Human-Centered Machine Learning with Visual Analytics.
UiB åpner et senter for datavitenskap: Center for Data Science (CEDAS).
Data science related talk by PD Dr. Steffen Oeltze-Jafra