nani1764/smai-mlp-model
AI model by nani1764
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This repository contains the selected Multi-Layer Perceptron (MLP) and IOC-NN models evaluated on the CIFAR-10 dataset. The MLP is implemented from scratch using NumPy, while the IOC-NN model is implemented using PyTorch. Model File: selectedmlpcifar10.npz Model Files: Weight Constraints For the IOC-NN model, the weights of layers with index $\ell \geq 2$ are constrained to be non-negative: $ W^{(\ell)} \geq 0, \qquad \ell \geq 2 $ The constraint is enforced using the following projection: $ \boxed{w \leftarrow e^{w-5}} $ Both models use the CIFAR-10 dataset, which consists of RGB images of dimensions $32 \times 32$. Each image is flattened into a one-dimensional feature vector: $ 32 \times 32 \times 3 = 3072 $ Therefore, the input dimension of both models is: $ \boxed{d{\text{input}} = 3072} $ The original pixel values are integers in the range $[0,255]$. They are scaled to the range $[0,1]$ using: $ \boxed{x{\text{scaled}} = \frac{x}{255.0}} $…
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Inside the original model card — Document outline
- Selected Models for SMAI Assignment 4 – Question 1
- 1. Model Architectures
- 1.1 Multi-Layer Perceptron (MLP)
- 1.2 IOC-NN
- 2. Dataset and Preprocessing
- 2.1 Input Dimensions
- 2.2 Pixel Scaling
- 2.3 Feature Standardization
- 3. Model Summary
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Model overview
nani1764/smai-mlp-model is a task-unspecified model repository published by nani1764 on Hugging Face. A library was not reported.
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- Created
- 2026-10-30T06:48:25.000Z
- Last modified
- 2026-10-30T06:48:25.000Z
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