Leveraging IA3 adapters for parameter-efficient logical deduction, Lightning AI
Investigates IA3 adapters for parameter efficient fine-tuning to enhance Llama-3’s logical deduction capabilities. (Apr. 2024)
Projects and Reports
Optimizing Reinforcement Policies for Aligning LLMs, Weights & Biases
Motivates the formulation of the proximal policy optimization algorithm and applies it for reinforcement learning from human feedback (RLHF) to align Google’s Gemma with human conversational preferences. (Mar. 2024)
Exploring Diffusion Models with JAX
Explores the mathematics and code of discrete diffusion models, assessing their effectiveness, applicability, and limitations. (Jun 2022)
Review Classification using Active Learning, Keras.io
Demonstrates the effectiveness of active learning in text classification tasks by implementing a ratio- based sampling approach, improving performance and suitability for industrial applications. (Oct 2021)
The Reality Behind the Optimization of Imaginary Variables - I, Weights & Biases
Examines how complex-valued neural networks enhance representations by experimenting with traditional mappings and more efficient complex vector techniques. (Jun 2021)
The Reality Behind the Optimization of Imaginary Variables - II, Weights & Biases
Explores circularity and holomorphicity constraints in complex-valued neural networks, showcasing the effectiveness of linear and widely linear networks for image-denoising. (Oct 2021)
MelGAN based Spectrogram Inversion using Feature Matching, Keras.io
Showcases a non-autoregressive model for spectral inversion utilizing a feature-matching discriminator, highlighting fast inference on dynamic inputs. (Sep 2021)