4 papers
Similarity of Neural Network Representations in Superposition
Sunny Liu, Habon Issa, André Longon +4
Comparing internal representations is a central goal in neuroscience and machine learning, but standard linear alignment metrics (Representational Similarity Analysis, Centered Ker…
Superposition disentanglement of neural representations reveals hidden alignment
André Longon, David Klindt, Meenakshi Khosla
The superposition hypothesis states that single neurons may participate in representing multiple features in order for the neural network to represent more features than it has neu…
Naturally Computed Scale Invariance in the Residual Stream of ResNet18
André Longon
An important capacity in visual object recognition is invariance to image-altering variables which leave the identity of objects unchanged, such as lighting, rotation, and scale. H…
Interpreting the Residual Stream of ResNet18
André Longon
A mechanistic understanding of the computations learned by deep neural networks (DNNs) is far from complete. In the domain of visual object recognition, prior research has illumina…