All Articles

Unveiling "Continuous Diffusion for Categorical Data Estimation for LLMs"

The CDCD framework harmoniously integrates continuous and discrete data generation methodologies, capitalizing on their respective strengths

Importance of Alignment in LLMs

Aligning LLM with human preferences is not just a technical feat, but a pivotal factor in ensuring the effectiveness of LLM applications.

A glimpse of the general agent–GATO

GATO can sense and act with different embodiments across a wide range of environments using a single neural network with common weights.

Exploring Geometric Deep Learning and its Impactful Applications

The key idea behind geometric deep learning is to develop neural network architectures that can operate directly on geometric data.

Beyond Unimodal: Embracing Multimodal Deep Learning for Enhanced AI

Multimodal deep learning is a subfield of machine learning that combines multiple sources of data to gain understanding.

Understanding CLIP

The reason why CLIP is so effective in zero-shot learning is because of the contrastive learning approach to jointly train a neural network.

Leveraging Reasoning-Modulated Representations for MRI and CT scan: A case study

Reasoning-modulated representations aim to create AI systems that are not just data-driven, but also capable of understanding and reasoning.

NAS + Reinforcement learning: A review

Neural architecture search (NAS) is a method for automatically discovering the best neural network architecture for a given task.

Perplexity in AI and Humans

Perplexity is a useful metric to evaluate models in Natural Language Processing (NLP).

Attention Probabilistic U-net

A new hybrid method to find anomalies in CT scans (on-going experiment) Image classification is not new to us and the same stands true...

Artificial intelligence for designing new materials

Understanding the material helps us to understand the working of the universe.

Cost-efficient method to predict 3D hemodynamics

The deep learning methods are inexpensive compare to modeling a cardiovascular hemodynamic system.

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