4 papers
On Divergence Measures for Training GFlowNets
Tiago da Silva, Eliezer de Souza da Silva, Diego Mesquita
Generative Flow Networks (GFlowNets) are amortized inference models designed to sample from unnormalized distributions over composable objects, with applications in generative mode…
Expert-Aided Causal Discovery of Ancestral Graphs
Tiago da Silva, Bruna Bazaluk, Eliezer de Souza da Silva +6
Causal discovery (CD) is an important component of many scientific applications, yet most techniques produce unreliable point estimates that often contradict expert knowledge. To m…
Augmented Memory Networks for Streaming-Based Active One-Shot Learning
Andreas Kvistad, Massimiliano Ruocco, Eliezer de Souza da Silva +1
One of the major challenges in training deep architectures for predictive tasks is the scarcity and cost of labeled training data. Active Learning (AL) is one way of addressing thi…
Time is of the Essence: a Joint Hierarchical RNN and Point Process Model for Time and Item Predictions
Bjørnar Vassøy, Massimiliano Ruocco, Eliezer de Souza da Silva +1
In recent years session-based recommendation has emerged as an increasingly applicable type of recommendation. As sessions consist of sequences of events, this type of recommendati…