This article reviews key techniques in continual learning, including parameter isolation, regularization, and replay methods.

Author: Dibin Mathew

We all need to hear them sometimes

This paper evaluates standard regularization methods, including Learning without Forgetting (LwF) and Synaptic Intelligence (SI).

I recently gave a talk on Clean Frontend Architecture, emphasizing maintainability and scalability [1]. After the talk, I received…

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This article evaluates various continual learning methods, including a novel disentangled learning framework, using the idSprites benchmark.

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Explore how disentangled learning separates generalization from memorization in continual learning.

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This paper presents Infinite dSprites, a novel framework for creating long continual learning benchmarks, alongside a conceptual disentangled learning approach.

This article critiques current class-incremental continual learning methods, highlighting their limitations and proposing solutions.

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A novel continual learning approach overcomes catastrophic forgetting by separating class-specific memorization from class-agnostic generalization.

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Tornado Cash is a privacy tool that can be used by anyone, everywhere as long as isn't fully censored... yet. Find out more in this article.

Explore the ethical challenges in AI development, from data privacy to bias, and discover how decentralized platforms like ICP are tackling these issues.

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BNB Chain Bridge launches with Celer, deBridge, and Stargate, boosting cross-chain interoperability and enhancing the UX for seamless asset transfers.