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20162024
most citedTime Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

48 citations · 51 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024

SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation

Prakhar Dixit, Tim Oates

Many students struggle with math word problems (MWPs), often finding it difficult to identify key information and select the appropriate mathematical operations. Schema-based instr…

cs.LG2024

TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks

Khondoker Murad Hossain, Tim Oates

As deep neural networks and the datasets used to train them get larger, the default approach to integrating them into research and commercial projects is to download a pre-trained…

cs.LG20231 cited

LLM Augmented Hierarchical Agents

Bharat Prakash, Tim Oates, Tinoosh Mohsenin

Solving long-horizon, temporally-extended tasks using Reinforcement Learning (RL) is challenging, compounded by the common practice of learning without prior knowledge (or tabula r…

cs.LG20231 cited

Recasting Self-Attention with Holographic Reduced Representations

Mohammad Mahmudul Alam, Edward Raff, Stella Biderman +2

In recent years, self-attention has become the dominant paradigm for sequence modeling in a variety of domains. However, in domains with very long sequence lengths the $\mathcal{O}…

cs.LG201648 cited

Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

Zhiguang Wang, Weizhong Yan, Tim Oates

We propose a simple but strong baseline for time series classification from scratch with deep neural networks. Our proposed baseline models are pure end-to-end without any heavy pr…