Reposted by Yoav Ger
This was a fantastic poster presentation!
At #NeurIPS? Curious about how RNNs learn differently in closed-loop (RL) vs. open-loop (supervised) settings?
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
December 5, 2025 at 6:56 PM
This was a fantastic poster presentation!
At #NeurIPS? Curious about how RNNs learn differently in closed-loop (RL) vs. open-loop (supervised) settings?
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
December 3, 2025 at 1:12 AM
At #NeurIPS? Curious about how RNNs learn differently in closed-loop (RL) vs. open-loop (supervised) settings?
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
Come by Poster #2107 on Thursday at 4:30 PM!
neurips.cc/virtual/2025...
Reposted by Yoav Ger
#NeuRIPS2025
Wanna find decision boundaries in your RNN? Or learn about Koopman Eigenfunctions? Come to my poster.
#2002
Wednesday, Dec 3, 11am-2pm.
Exhb. Hall C,D,E
San Diego
neurips.cc/virtual/2025...
Wanna find decision boundaries in your RNN? Or learn about Koopman Eigenfunctions? Come to my poster.
#2002
Wednesday, Dec 3, 11am-2pm.
Exhb. Hall C,D,E
San Diego
neurips.cc/virtual/2025...
NeurIPS Poster Finding separatrices of dynamical flows with Deep Koopman EigenfunctionsNeurIPS 2025
neurips.cc
December 2, 2025 at 5:47 PM
#NeuRIPS2025
Wanna find decision boundaries in your RNN? Or learn about Koopman Eigenfunctions? Come to my poster.
#2002
Wednesday, Dec 3, 11am-2pm.
Exhb. Hall C,D,E
San Diego
neurips.cc/virtual/2025...
Wanna find decision boundaries in your RNN? Or learn about Koopman Eigenfunctions? Come to my poster.
#2002
Wednesday, Dec 3, 11am-2pm.
Exhb. Hall C,D,E
San Diego
neurips.cc/virtual/2025...
Reposted by Yoav Ger
Are world models necessary to achieve human-level agents, or is there a model-free short-cut?
Our new #ICML2025 paper tackles this question from first principles, and finds a surprising answer, agents _are_ world models… 🧵
arxiv.org/abs/2506.01622
Our new #ICML2025 paper tackles this question from first principles, and finds a surprising answer, agents _are_ world models… 🧵
arxiv.org/abs/2506.01622
June 4, 2025 at 3:48 PM
Are world models necessary to achieve human-level agents, or is there a model-free short-cut?
Our new #ICML2025 paper tackles this question from first principles, and finds a surprising answer, agents _are_ world models… 🧵
arxiv.org/abs/2506.01622
Our new #ICML2025 paper tackles this question from first principles, and finds a surprising answer, agents _are_ world models… 🧵
arxiv.org/abs/2506.01622
Reposted by Yoav Ger
All our motor control modelling efforts focus on closed-loop systems for this reason:
"...closed-loop and open-loop training produce fundamentally different learning dynamics, even when using identical architectures and converging to the same final solution."
arxiv.org/abs/2505.13567
"...closed-loop and open-loop training produce fundamentally different learning dynamics, even when using identical architectures and converging to the same final solution."
arxiv.org/abs/2505.13567
Learning Dynamics of RNNs in Closed-Loop Environments
Recurrent neural networks (RNNs) trained on neuroscience-inspired tasks offer powerful models of brain computation. However, typical training paradigms rely on open-loop, supervised settings, whereas ...
arxiv.org
May 29, 2025 at 5:28 PM
All our motor control modelling efforts focus on closed-loop systems for this reason:
"...closed-loop and open-loop training produce fundamentally different learning dynamics, even when using identical architectures and converging to the same final solution."
arxiv.org/abs/2505.13567
"...closed-loop and open-loop training produce fundamentally different learning dynamics, even when using identical architectures and converging to the same final solution."
arxiv.org/abs/2505.13567