---
title: "Published the DICLE paper"
description: "Dynamic Input-Correlated Layer Execution (DICLE): a theoretical framework for speeding up deep learning inference by skipping layers based on input correlation, published in IJCRT."
url: "https://meghrajjare.in/timeline/dicle-publication/"
---

# Published the DICLE paper

> Dynamic Input-Correlated Layer Execution (DICLE): a theoretical framework for speeding up deep learning inference by skipping layers based on input correlation, published in IJCRT.

- **Timeline step:** 8
- **Date:** April 2026
- **Category:** Research
- **Organization:** International Journal of Creative Research Thoughts (IJCRT)
- **Link:** [https://ijcrt.org](https://ijcrt.org)

## Abstract

In modern deep learning architectures, computational efficiency is a primary bottleneck, particularly when deploying large-scale neural networks to edge devices or real-time systems. **Dynamic Input-Correlated Layer Execution (DICLE)** is proposed as a theoretical framework designed to optimize inference latency by dynamically bypassing or executing specific layers of a deep neural network based on the statistical correlation of input features.

By evaluating the spatial and temporal correlation of input representations at runtime, the DICLE framework determines whether down-stream layers will yield statistically significant updates to the activation state. If the correlation exceeds a predefined threshold, redundant layer computations are bypassed, and intermediate state estimates are projected forward, saving substantial floating-point operations (FLOPs) without compromising accuracy.

## Key Contributions

- **Input-Correlation Metric:** Formulated a mathematical metric to evaluate feature correlation across layer interfaces dynamically at runtime.
- **State Projection Mechanics:** Developed a mathematical model to approximate outputs of skipped layers based on correlation profiles, preventing gradient disconnects and state corruption.
- **Dynamic Routing Algorithm:** Outlined an execution engine that adjusts threshold sensitivities adaptively, matching hardware thermal throttling or latency requirements.

## Publication Details

- **Journal:** International Journal of Creative Research Thoughts (IJCRT)
- **Paper ID:** IJCRT26A4022
- **Publication Date:** April 2026
- **Co-Authors:** Tanish Jagtap, Vidish Bajpai