1.2k citations · 1.5k across the 6 of their papers we have counts for
7 papers
Deep Learning for Anomaly Detection: A Survey
Raghavendra Chalapathy, Sanjay Chawla
Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The aim of this survey is two-fold, firstly we present a…
Group Anomaly Detection using Deep Generative Models
Raghavendra Chalapathy, Edward Toth, Sanjay Chawla
Unlike conventional anomaly detection research that focuses on point anomalies, our goal is to detect anomalous collections of individual data points. In particular, we perform gro…
Anomaly Detection using One-Class Neural Networks
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
We propose a one-class neural network (OC-NN) model to detect anomalies in complex data sets. OC-NN combines the ability of deep networks to extract a progressively rich representa…
Robust, Deep and Inductive Anomaly Detection
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
PCA is a classical statistical technique whose simplicity and maturity has seen it find widespread use as an anomaly detection technique. However, it is limited in this regard by b…
Bidirectional LSTM-CRF for Clinical Concept Extraction
Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi
Automated extraction of concepts from patient clinical records is an essential facilitator of clinical research. For this reason, the 2010 i2b2/VA Natural Language Processing Chall…
Bidirectional LSTM-CRF for Clinical Concept Extraction
Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi
Extraction of concepts present in patient clinical records is an essential step in clinical research. The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for clinic…
An Investigation of Recurrent Neural Architectures for Drug Name Recognition
Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi
Drug name recognition (DNR) is an essential step in the Pharmacovigilance (PV) pipeline. DNR aims to find drug name mentions in unstructured biomedical texts and classify them into…