Saisubramaniam Gopalakrishnan

According to our database, Saisubramaniam Gopalakrishnan authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Leveraging Latent Evolutionary Optimization for Targeted Molecule Generation.

Siddartha Reddy, Sai Prakash MV, Varun V, Vishal Vaddina, Saisubramaniam Gopalakrishnan

CoRR, 2024

Automated Tailoring of Large Language Models for Industry-Specific Downstream Tasks.

Shreya Saxena, Siva Prasad, Muneeswaran I, Advaith Shankar, Varun V, Saisubramaniam Gopalakrishnan, Vishal Vaddina

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Accelerating Pharmacovigilance using Large Language Models.

Mukkamala Venkata Sai Prakash, Ganesh Parab, Meghana Veeramalla, Siddartha Reddy, Varun V, Saisubramaniam Gopalakrishnan, Vishal Pagidipally, Vishal Vaddina

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Mitigating Factual Inconsistency and Hallucination in Large Language Models.

Muneeswaran I, Advaith Shankar, Varun V, Saisubramaniam Gopalakrishnan, Vishal Vaddina

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Leveraging Latent Evolutionary Optimization for Targeted Molecule Generation.

Siddartha Reddy, Sai Prakash MV, V. Varun, Saisubramaniam Gopalakrishnan, Vishal Vaddina

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

Minimizing Factual Inconsistency and Hallucination in Large Language Models.

Muneeswaran I, Shreya Saxena, Siva Prasad, Mukkamala Venkata Sai Prakash, Advaith Shankar, Varun V, Vishal Vaddina, Saisubramaniam Gopalakrishnan

CoRR, 2023

Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction.

Mukkamala Venkata Sai Prakash, Siddartha Reddy, Ganesh Parab, Varun V, Vishal Vaddina, Saisubramaniam Gopalakrishnan

Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

2022

Classify and generate: Using classification latent space representations for image generations.

Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi

Neurocomputing, 2022

Knowledge Capture and Replay for Continual Learning.

Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Haytham M. Fayek, Savitha Ramasamy, Arulmurugan Ambikapathi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

2021

Task-Agnostic Continual Learning Using Base-Child Classifiers.

Pranshu Ranjan Singh, Saisubramaniam Gopalakrishnan, Qiao ZhongZheng, Ponnuthurai N. Suganthan, Savitha Ramasamy, Arulmurugan Ambikapathi

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

Classification Representations Can be Reused for Downstream Generations.

Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi

CoRR, 2020

Hybrid Deep Reinforced Regression Framework for Cardio-Thoracic Ratio Measurement.

Pranshu Ranjan Singh, Saisubramaniam Gopalakrishnan, Ivan Ho Mien, Arulmurugan Ambikapathi

Proceedings of the IEEE International Conference on Image Processing, 2020

Improving 3D Brain Tumor Segmentation With Predict-Refine Mechanism Using Saliency And Feature Maps.

Tin Lay Nwe, Oo Zaw Min, Saisubramaniam Gopalakrishnan, Dongyun Lin, Shitala Prasad, Sheng Dong, Yiqun Li, Ramanpreet Singh Pahwa

Proceedings of the IEEE International Conference on Image Processing, 2020