5 citations · 5 across the 1 of their papers we have counts for
4 papers
Approximate Bayesian Inference via Bitstring Representations
Aleksanteri Sladek, Martin Trapp, Arno Solin
The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in…
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel +4
Mixture models are traditionally represented and learned by adding several distributions as components. Allowing mixtures to subtract probability mass or density can drastically re…
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
Mathias Löwe, Jennifer Villareale, Evan Freed +3
Applying neural network (NN) methods in games can lead to various new and exciting game dynamics not previously possible. However, they also lead to new challenges such as the lack…
iNNk: A Multi-Player Game to Deceive a Neural Network
Jennifer Villareale, Ana Acosta-Ruiz, Samuel Arcaro +10
This paper presents iNNK, a multiplayer drawing game where human players team up against an NN. The players need to successfully communicate a secret code word to each other throug…