347 citations · 514 across the 18 of their papers we have counts for
32 papers
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss
Vedant Shah, Aditya Agrawal, Lovekesh Vig +3
We are interested in neurosymbolic systems consisting of a high-level symbolic layer for explainable prediction in terms of human-intelligible concepts; and a low-level neural laye…
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
Vishwa Shah, Aditya Sharma, Gautam Shroff +3
Analogical Reasoning problems challenge both connectionist and symbolic AI systems as these entail a combination of background knowledge, reasoning and pattern recognition. While s…
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions
Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra +2
We consider a sequence of related multivariate time series learning tasks, such as predicting failures for different instances of a machine from time series of multi-sensor data, o…
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression
Diksha Garg, Pankaj Malhotra, Anil Bhatia +3
We consider learning a trading agent acting on behalf of the treasury of a firm earning revenue in a foreign currency (FC) and incurring expenses in the home currency (HC). The goa…
DRTCI: Learning Disentangled Representations for Temporal Causal Inference
Garima Gupta, Lovekesh Vig, Gautam Shroff
Medical professionals evaluating alternative treatment plans for a patient often encounter time varying confounders, or covariates that affect both the future treatment assignment…
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems
Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash +3
The ability to recognise and make analogies is often used as a measure or test of human intelligence. The ability to solve Bongard problems is an example of such a test. It has als…