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20182026
most citedActive Predicting Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems

2 citations · 5 across the 17 of their papers we have counts for

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cs.LG2024

Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks

Ankur Mali, Tommaso Salvatori, Alexander Ororbia

Energy-based learning algorithms, such as predictive coding (PC), have garnered significant attention in the machine learning community due to their theoretical properties, such as…

cs.LG2024

A Unified Framework for Continual Learning and Unlearning

Romit Chatterjee, Vikram Chundawat, Ayush Tarun +2

Continual learning and machine unlearning are crucial challenges in machine learning, typically addressed separately. Continual learning focuses on adapting to new knowledge while…

cs.LG2024

Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps

Hitesh Vaidya, Travis Desell, Ankur Mali +1

An intelligent system capable of continual learning is one that can process and extract knowledge from potentially infinitely long streams of pattern vectors. The major challenge t…

cs.LG2024

Stable and Robust Deep Learning By Hyperbolic Tangent Exponential Linear Unit (TeLU)

Alfredo Fernandez, Ankur Mali

In this paper, we introduce the Hyperbolic Tangent Exponential Linear Unit (TeLU), a novel neural network activation function, represented as . TeLU is de…

cs.LG2024

Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network

Neisarg Dave, Daniel Kifer, C. Lee Giles +1

This paper analyzes two competing rule extraction methodologies: quantization and equivalence query. We trained RNN models, extracting DFA with a quantization approa…

cs.LG2023

On the Computational Complexity and Formal Hierarchy of Second Order Recurrent Neural Networks

Ankur Mali, Alexander Ororbia, Daniel Kifer +1

Artificial neural networks (ANNs) with recurrence and self-attention have been shown to be Turing-complete (TC). However, existing work has shown that these ANNs require multiple t…