Python codes for the experiment about LSTM Inefficiency in Long-Term Dependencies Regression Problems
This is the repository of the source code of DLTP Assignment - 2, 5th Semester, IIITH
A comparative experiment between RNN and LSTM models to evaluate their ability to perform noise-robust sequence prediction. The project tests short-term vs long-term memory by reconstructing clean input sequences from noisy data, showing how LSTM outperforms RNN under long-dependency conditions.
Implemented RNN and LSTM networks using PyTorch and trained them to classify numerical sequences to compare and analyze their performance on detecting long term dependencies and temporal order in the input sequences
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