Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification | ScienceToStartup | ScienceToStartup

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References (15)

[1]

Variance-Based Pruning for Accelerating and Compressing Trained Networks

2025Uranik Berisha, Jens Mehnert et al.

[2]

Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

2023Atticus Geiger, Zhengxuan Wu et al.

[3]

Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability

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"A novel method to discover causal abstractions in neural networks using mechanism sparsification."

Causal Inference•Score: 2•View PDF ↗

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Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification

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References (15)

Founder's Pitch

"A novel method to discover causal abstractions in neural networks using mechanism sparsification."

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Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification

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References (15)

Founder's Pitch

"A novel method to discover causal abstractions in neural networks using mechanism sparsification."

Commercial Viability Breakdown

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