69 citations · 74 across the 7 of their papers we have counts for
7 papers
How Weight Resampling and Optimizers Shape the Dynamics of Continual Learning and Forgetting in Neural Networks
Lapo Frati, Neil Traft, Jeff Clune +1
Recent work in continual learning has highlighted the beneficial effect of resampling weights in the last layer of a neural network (``zapping"). Although empirical results demonst…
Networks of Binary Necklaces Induced by Elementary Cellular Automata Rules
Lapo Frati, Csenge Petak, Nick Cheney
Elementary cellular automata deterministically map a binary sequence to another using simple local rules. Visualizing the structure of this mapping is difficult because the number…
Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning
Lapo Frati, Neil Traft, Jeff Clune +1
This work identifies a simple pre-training mechanism that leads to representations exhibiting better continual and transfer learning. This mechanism -- the repeated resetting of we…
Coping with seasons: evolutionary dynamics of gene networks in a changing environment
Csenge Petak, Lapo Frati, Melissa H. Pespeni +1
In environments that vary frequently and unpredictably, bet-hedgers can overtake the population. Diversifying bet-hedgers have a diverse set of offspring so that, no matter the con…
A good body is all you need: avoiding catastrophic interference via agent architecture search
Joshua Powers, Ryan Grindle, Lapo Frati +1
In robotics, catastrophic interference continues to restrain policy training across environments. Efforts to combat catastrophic interference to date focus on novel neural architec…
Learning to Continually Learn
Shawn Beaulieu, Lapo Frati, Thomas Miconi +4
Continual lifelong learning requires an agent or model to learn many sequentially ordered tasks, building on previous knowledge without catastrophically forgetting it. Much work ha…