Update README

Author: AnirudhBHarish

README.md

@@ -17,6 +17,7 @@ Algorithms that shine in this setting in terms of both model size and compute, n
  - **EMI-RNN**: Training routine to recover the critical signature from time series data for faster and accurate RNN predictions.
  - **Shallow RNN**: A meta-architecture for training RNNs that can be applied to streaming data.
  - **FastRNN & FastGRNN - FastCells**: **F**ast, **A**ccurate, **S**table and **T**iny (**G**ated) RNN cells.
+ - **Conv1D**: 1-D regular and low-rank convolution architectures for time-series data.
  - **DROCC**: **D**eep **R**obust **O**ne-**C**lass **C**lassfiication for training robust anomaly detectors.
 
 These algorithms can train models for classical supervised learning problems