1.3k citations · 2.9k across the 32 of their papers we have counts for
4 papers · 1 filter
Scalable agent alignment via reward modeling: a research direction
Jan Leike, David Krueger, Tom Everitt +3
One obstacle to applying reinforcement learning algorithms to real-world problems is the lack of suitable reward functions. Designing such reward functions is difficult in part bec…
Uncertainty in Multitask Transfer Learning
Alexandre Lacoste, Boris Oreshkin, Wonchang Chung +3
Using variational Bayes neural networks, we develop an algorithm capable of accumulating knowledge into a prior from multiple different tasks. The result is a rich and meaningful p…
Neural Autoregressive Flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste +1
Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to…
Nested LSTMs
Joel Ruben Antony Moniz, David Krueger
We propose Nested LSTMs (NLSTM), a novel RNN architecture with multiple levels of memory. Nested LSTMs add depth to LSTMs via nesting as opposed to stacking. The value of a memory…