48 citations · 55 across the 5 of their papers we have counts for
5 papers
Through a Steerable Lens: Magnifying Neural Network Interpretability via Phase-Based Extrapolation
Farzaneh Mahdisoltani, Saeed Mahdisoltani, Roger B. Grosse +1
Understanding the internal representations and decision mechanisms of deep neural networks remains a critical open challenge. While existing interpretability methods often identify…
Natural Gradient Variational Inference with Gaussian Mixture Models
Farzaneh Mahdisoltani
Bayesian methods estimate a measure of uncertainty by using the posterior distribution. One source of difficulty in these methods is the computation of the normalizing constant. Ca…
Learning Representations for Predicting Future Activities
Mohammadreza Zolfaghari, Özgün Çiçek, Syed Mohsin Ali +3
Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics…
Hierarchical Video Understanding
Farzaneh Mahdisoltani, Roland Memisevic, David Fleet
We introduce a hierarchical architecture for video understanding that exploits the structure of real world actions by capturing targets at different levels of granularity. We desig…
On the effectiveness of task granularity for transfer learning
Farzaneh Mahdisoltani, Guillaume Berger, Waseem Gharbieh +2
We describe a DNN for video classification and captioning, trained end-to-end, with shared features, to solve tasks at different levels of granularity, exploring the link between g…