Search Results for author:
Found 5 papers, 3 papers with code
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
Due to the special properties of S5 layers, our method can train in parallel and predict next world states iteratively during imagination.
On the detrimental effect of invariances in the likelihood for variational inference
Then, we transfer our analysis of the linear model to neural networks.
A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!
Abstract We present PAC-Bayesian bounds for the generalisation error of the K-nearest-neighbour classifier (K-NN).
CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact Data
We present CRISP (COVID-19 Risk Score Prediction), a probabilistic graphical model for COVID-19 infection spread through a population based on the SEIR model where we assume access to (1) mutual contacts between pairs of individuals across time across various channels (e. g., Bluetooth contact traces), as well as (2) test outcomes at given times for infection, exposure and immunity tests.
TrueSkill Through Time: Revisiting the History of Chess
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering.
