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NORD-F : addressing near-oods for robust classification through disentanglement representation learning for fine grained datasets

Sharma, Ishika; Prasad, Ranjitha (advisor) (IIIT-Delhi, 2024-07-29)

Out-of-Distribution (OoD) detection has emerged as a crucial aspect in machine learning, essential for ensuring the resilience and reliability of models deployed in real-world scenarios. Traditional methods excel at ...

Asymmetric high-density low leakage SRAM cells

Shroti, Ajay; Grover, Anuj (Advisor) (IIIT-Delhi, 2024-05-15)

Embedded memories occupy up to 70% of the area and account for 30-50% power consumption in advanced digital SoCs. A large part of this power is leakage power. Therefore, high-density, low-leakage SRAM cells are desirable. ...

Federated learning with distribution models

Reddy, Gunjapalli Sravani; Chatterjee, Bapi (Advisor) (IIIT-Delhi, 2024-06-14)

This thesis investigates the integration of Mixture Density Networks (MDNs) within Federated Learning (FL) frameworks to tackle challenges in data privacy, security, and model robustness, focusing on Automatic Speech ...

A digital honor code : detecting academic dishonesty with keystroke dynamics

Kundu, Debnath; Shah, Rajiv Ratn (Advisor); Kumar, Rajesh (Advisor) (IIIT-Delhi, 2024-05-20)

As educational assessments migrate to digital platforms, ensuring academic integrity becomes crucial. Traditional plagiarism detection systems struggle to catch instances of intelligent cheating, especially when students ...

Participation strategies in federated learning with heterogeneous client communications

Agrawal, Shubham; Chatterjee, Bapi (Advisor) (IIIT-Delhi, 2024-06-01)

In cross-device federated learning (FL) [1], a machine learning model is developed by leveraging communication between a central server and numerous edge device clients. In practical scenarios, the ability of these edge ...

Quaternion-enhanced neural networks : a new paradigm for audio processing efficiency

Chaudhary, Aryan; Abrol, Vinayak (Advisor) (IIIT-Delhi, 2024-05-01)

This thesis explores the integration of quaternion algebra into neural network architectures to enhance their efficiency for diverse audio processing tasks. Quaternion-based transformations are employed to achieve structural ...

Taxonomy completion via sector hierarchy

Talukdar, Indraayudh; Akhtar, Md Shad (Advisor) (IIIT-Delhi, 2024-07-01)

Taxonomy is a hierarchical structure that deals with knowledge. It can be perceivedas Knowledge graph with all the relations being only ’is-a’. Automatic creation of taxonomies can be achieved by creation scratch, by ...

Exploration of continual learning paradigm for large-scale speaker verification systems

Verma, Akash; Abrol, Vinayak (Advisor) (IIIT-Delhi, 2024-05-21)

Speaker verification (SV) focuses on confirming or denying the claimed identity of a speaker. It is a one-to-one comparison between the test utterance and the claimant’s stored reference voice sample. This process is ...

Indian legal case judgment document mining : semantic segmentation and information extraction

Das, Antara; Goyal, Vikram (Advisor) (IIIT-Delhi, 2024-05-01)

Developing NLP-based techniques to automate tasks in the Indian legal domain is highly demanding due to the enormously increasing volume of legal text documents, intricate legal terminologies, and the need for efficient ...

Patterns and problems : analyzing document layouts and improving mathematical reasoning of llms

Gupta, Mohit; Shah, Rajiv Ratn (Advisor) (IIIT-Delhi, 2024-05-08)

Documents play a pivotal role in conveying information, serving as integral carriers of knowledge across various domains. Their importance lies in their ability to encapsulate ideas, facts, and insights, thereby facilitating ...

Federated distribution learning

Bansal, Mehak; Chatterjee, Bapi (Advisor) (IIIT-Delhi, 2024-01-19)

Distribution Learning is a form of machine learning which involves the distribution of data across in a network having multiple devices. Each node is trained independently, and then combined the results to generate a model ...

VT-Nood : vision transformer based near ood detection in fine-grained datasets

Dey, Kaushik; Prasad, Ranjitha (Advisor) (IIIT-Delhi, 2024-08-01)

Machine Learning models output high confidence scores when provided with input samples that belong to the input data distribution, referred to as in-distribution (ID)samples. However, when presented with an Out of Distribution ...

A deep learning approach for predicting antimicrobial resistance across various bacterial species using whole genome sequence

Muddemmanavar, Prateeksha; Sengupta, Debarka (Advisor) (IIIT-Delhi, 2024-05-01)

Antimicrobial resistance (AMR) presents an immediate threat to public health as microorganismsevolve to resist antimicrobial drugs, leading to challenging or untreatable infections.AMR-related costs could exceed 1 trillion ...

Deep learning based molecule generation for developing novel therapeutics for neurodegenerative diseases

Joshi, Piyush; Murugan, N. Arul (Advisor) (IIIT-Delhi, 2024-05-01)

Deep learning models and generative AI have revolutionized drug discovery, especially with regard to neurodegenerative diseases like Alzheimer's. The developing of canonical SMILES (Simplified Molecular Input Line Entry ...

Evaluation of state-space models and widely used architectures in deep learning for heterogenous tasks

Paul, Ankush; Kumar, Vibhor (Advisor) (IIIT-Delhi, 2024-08-01)

Novel framework for predicting multitarget antifungal drugs against pathogenic fungi

S, Karthika; Ahuja, Gaurav (Advisor) (IIIT-Delhi, 2024-06)

Pathogenic fungal diseases have become a global threat to human health in immunocompromised individuals. With increasing mortality rates due to systemic infections and limited availability of antifungal classes, it is ...

Identifying novel caloric restriction mimetics using generative AI

Nanshi, Jeet; Ahuja, Gaurav (Advisor) (IIIT-Delhi, 2024-01-20)

In the contemporary era, anti-aging stands as a prominent research focus. Recognizing the impact of diet on aging, investigations into caloric restriction methods have emerged as a promising and effective approach in ...

Machine learning and tanimoto similarity based virtual screening of chemical libraries to develop novel PD therapeutics

Singhal, Divyanshi; Murugan, N Arul (Advisor) (IIIT-Delhi, 2024-05-01)

Parkinson's disease is a prevalent neurodegenerative disorder that affects a significant portion of the aging population worldwide. The etiology of Parkinson's disease involves the accumulation of misfolded proteins, ...

Developing machine learning and deep learning models for predicting the thermal stability of proteins

Singh, Surabhi; Murugan, N Arul (Advisor) (IIIT-Delhi, 2024-05-01)

The accurate prediction of protein stability temperatures is essential for numerous applications in bioinformatics and biotechnology. In this study, we utilized a multifaceted computational approach to develop predictive ...

Insights into the mechanisms of resistance to axitinib in cancer cell lines

Patni, Khyati; Dhanjal, Jaspreet Kaur (Advisor) (IIIT-Delhi, 2024-06)

Along with the remarkable success stories in the evolutionary journey of targeted cancer treatment, there are examples where the targeted therapies failed to match the expectations. There have been multiple reports of ...

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