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View Code? Open in Web Editor NEW[NeurIPS 2022] FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation
License: MIT License
[NeurIPS 2022] FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation
License: MIT License
Thank you for the great work. Is it possible to provide the code for your experiments.
I am interested to use it in one of my experiments. Thanks in advance.
--Amit
First of all, this work is fantastic.
Secondly, the paper has not mentioned any experiment using FiLM-Ensemble with different inputs (like point clouds, for example).
I'm currently working on uncertainty estimation in place recognition and I'm using explicit ensemble to do that. With FiLM, I can create an implicit ensemble (actually using PointNet as the backbone and aggregation layer like NetVLAD), but I have a problem with GPU memory overflow.
To my understanding, the problem comes from during the forwarding pass, where there is the repeat_interleave call.
Is this the efficient way to feed the model with CBN layers?
Have you thought about more memory-efficient ways to feed the model?
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