47 citations
- D. Bhattacharya2 profiles4 · h 29
- S. M. Bhattacharjee4 · h 18
- Suratna Das2 profiles4 · h 2
- Aritra Das3 · h 1
- Dipankar Bhattacharya2 profiles3 · h 4
- Somak Raychaudhury2 profiles3 · h 35
- U. physics3 · h 29
- V. Bhalerao3 profiles3 · h 32
- Yashas Shende3 · h 1
- A. A. Nizami2 · h 12
- Arghya Pathak2 · h 1
- D. Gupta2 · h 1
- Inter-University Centre for Astronomy and AstrophysicsIN11 papers
- Indian Institute of Technology BombayIN5 papers
- Kavli Institute for Particle Astrophysics and CosmologyUS4 papers
- Indian Institute of Technology KharagpurIN3 papers
- Physical Research LaboratoryIN3 papers
- California Institute of TechnologyUS2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Goddard Space Flight CenterUS2 papers
- Indian Institute of AstrophysicsIN2 papers
- Indian Institute of Science Education and Research MohaliIN2 papers
- Indian Institute of Technology GandhinagarIN2 papers
- Stanford UniversityUS2 papers
4 papers · 1 filter
AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret
Saptarishi Dhanuka, Sarvesh Iyer, Manmeet Singh +5
Recent advances in machine learning have produced probabilistic weather forecasting models comparable to state-of-the-art numerical weather predictors. But no model consistently do…
Joint 3D Gravity and Magnetic Inversion via Rectified Flow and Ginzburg-Landau Guidance
Dhruman Gupta, Yashas Shende, Aritra Das +2
Subsurface ore detection is of paramount importance given the rising depletion of shallow mineral resources in recent years. It is crucial to explore approaches that go beyond the…
Physics Aware Neural Networks: Denoising for Magnetic Navigation
Aritra Das, Yashas Shende, Muskaan Chugh +3
Magnetic-anomaly navigation, leveraging small-scale variations in the Earth's magnetic field, is a promising alternative when GPS is unavailable or compromised. Airborne systems fa…
Oscillators Are All You Need: Irregular Time Series Modelling via Damped Harmonic Oscillators with Closed-Form Solutions
Yashas Shende, Aritra Das, Reva Laxmi Chauhan +2
Transformers excel at time series modelling through attention mechanisms that capture long-term temporal patterns. However, they assume uniform time intervals and therefore struggl…