36 citations · 69 across the 8 of their papers we have counts for
8 papers
Attention Drift: What Autoregressive Speculative Decoding Models Learn
Doğaç Eldenk, Payal Mohapatra, Yigitcan Comlek +3
Speculative decoding accelerates LLM inference by drafting future tokens with a small model, but drafter models degrade sharply under template perturbation and long-context inputs.…
Multi-task Modeling for Engineering Applications with Sparse Data
Yigitcan Comlek, R. Murali Krishnan, Sandipp Krishnan Ravi +7
Modern engineering and scientific workflows often require simultaneous predictions across related tasks and fidelity levels, where high-fidelity data is scarce and expensive, while…
Understanding process-structure-property relation for elastoplastic behavior of polymer nanocomposites with agglomeration anomalies and gradient interphase percolation
Prajakta Prabhune, Anlan Chen, Yigitcan Comlek +2
For polymer nanocomposites, disordered microstructural nature makes processing control and tailoring properties to desired values a challenge. Understanding process-structure-prope…
Heterogenous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process
Yigitcan Comlek, Sandipp Krishnan Ravi, Piyush Pandita +3
Artificial intelligence and machine learning frameworks have served as computationally efficient mapping between inputs and outputs for engineering problems. These mappings have en…
Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process
Sandipp Krishnan Ravi, Yigitcan Comlek, Arjun Pathak +9
With the advent of artificial intelligence and machine learning, various domains of science and engineering communities have leveraged data-driven surrogates to model complex syste…
Mixed-Variable Global Sensitivity Analysis For Knowledge Discovery And Efficient Combinatorial Materials Design
Yigitcan Comlek, Liwei Wang, Wei Chen
Global Sensitivity Analysis (GSA) is the study of the influence of any given inputs on the outputs of a model. In the context of engineering design, GSA has been widely used to und…
A Latent Variable Approach for Non-Hierarchical Multi-Fidelity Adaptive Sampling
Yi-Ping Chen, Liwei Wang, Yigitcan Comlek +1
Multi-fidelity (MF) methods are gaining popularity for enhancing surrogate modeling and design optimization by incorporating data from various low-fidelity (LF) models. While most…
Rapid Design of Top-Performing Metal-Organic Frameworks with Qualitative Representations of Building Blocks
Yigitcan Comlek, Thang Duc Pham, Randall Snurr +1
Data-driven materials design often encounters challenges where systems require or possess qualitative (categorical) information. Metal-organic frameworks (MOFs) are an example of s…