Search Results for author: Aaditya Prakash

Found 12 papers, 4 papers with code

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology

no code implementations3 Jun 2022 Syed Ashar Javed, Dinkar Juyal, Harshith Padigela, Amaro Taylor-Weiner, Limin Yu, Aaditya Prakash

Our Additive MIL models enable spatial credit assignment such that the contribution of each region in the image can be exactly computed and visualized.

Decision Making Multiple Instance Learning

Rethinking Machine Learning Model Evaluation in Pathology

no code implementations11 Apr 2022 Syed Ashar Javed, Dinkar Juyal, Zahil Shanis, Shreya Chakraborty, Harsha Pokkalla, Aaditya Prakash

Machine Learning has been applied to pathology images in research and clinical practice with promising outcomes.

BIG-bench Machine Learning

RePr: Improved Training of Convolutional Filters

1 code implementation CVPR 2019 Aaditya Prakash, James Storer, Dinei Florencio, Cha Zhang

We show that by temporarily pruning and then restoring a subset of the model's filters, and repeating this process cyclically, overlap in the learned features is reduced, producing improved generalization.

Protecting JPEG Images Against Adversarial Attacks

no code implementations2 Mar 2018 Aaditya Prakash, Nick Moran, Solomon Garber, Antonella DiLillo, James Storer

As deep neural networks (DNNs) have been integrated into critical systems, several methods to attack these systems have been developed.

DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference

no code implementations NAACL 2018 Reza Ghaeini, Sadid A. Hasan, Vivek Datla, Joey Liu, Kathy Lee, Ashequl Qadir, Yuan Ling, Aaditya Prakash, Xiaoli Z. Fern, Oladimeji Farri

Instead, we propose a novel dependent reading bidirectional LSTM network (DR-BiLSTM) to efficiently model the relationship between a premise and a hypothesis during encoding and inference.

Natural Language Inference

Deflecting Adversarial Attacks with Pixel Deflection

3 code implementations CVPR 2018 Aaditya Prakash, Nick Moran, Solomon Garber, Antonella DiLillo, James Storer

Despite their robustness to natural variations, image pixel values can be manipulated, via small, carefully crafted, imperceptible perturbations, to cause a model to misclassify images.

Adversarial Attack

Semantic Perceptual Image Compression using Deep Convolution Networks

3 code implementations27 Dec 2016 Aaditya Prakash, Nick Moran, Solomon Garber, Antonella DiLillo, James Storer

Here, we present a powerful cnn tailored to the specific task of semantic image understanding to achieve higher visual quality in lossy compression.

Image Compression object-detection +2

Condensed Memory Networks for Clinical Diagnostic Inferencing

no code implementations6 Dec 2016 Aaditya Prakash, Siyuan Zhao, Sadid A. Hasan, Vivek Datla, Kathy Lee, Ashequl Qadir, Joey Liu, Oladimeji Farri

We introduce condensed memory neural networks (C-MemNNs), a novel model with iterative condensation of memory representations that preserves the hierarchy of features in the memory.

Neural Clinical Paraphrase Generation with Attention

no code implementations WS 2016 Sadid A. Hasan, Bo Liu, Joey Liu, Ashequl Qadir, Kathy Lee, Vivek Datla, Aaditya Prakash, Oladimeji Farri

Paraphrase generation is important in various applications such as search, summarization, and question answering due to its ability to generate textual alternatives while keeping the overall meaning intact.

Document Summarization Information Retrieval +5

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