Akash Srivastava
24 papers · 2017–2026 · 5 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (5) 🏃 Academic Marathon (9) 🌈 Renaissance Researcher (9)
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Hot Topic Early Bird
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Cross-Pollinator
(13)
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Renaissance Researcher
(9)
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Keyword Collector
(106)
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Century Club
(24)
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(10)
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Prolific Year
(8)
Conferences
NIPS (12)
ICLR (5)
ICML (3)
WACV (3)
EMNLP (1)
Top co-authors
Keywords
variational inference
(4)
neural network
(3)
diffusion model
(3)
uncertainty quantification
(2)
contrastive learning
(2)
representation learning
(2)
extracellular recordings
(2)
variational autoencoder
(2)
spike sorting
(2)
offline reinforcement learning
(1)
bayesian inference
(1)
ensemble learning
(1)
hierarchical planning
(1)
bayesian nonparametrics
(1)
causal inference
(1)
transfer learning
(1)
neural architecture search
(1)
neural dynamics
(1)
image editing
(1)
image reconstruction
(1)
Papers
DICE: Discrete Inversion Enabling Controllable Editing for Masked Generative Models
WACV 2026
Hopscotch: Discovering and Skipping Redundancies in Language Models
EMNLP 2025
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs
ICLR 2025
SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models
WACV 2025
Curiosity-driven Red-teaming for Large Language Models
ICLR 2024
ProxEdit: Improving Tuning-Free Real Image Editing With Proximal Guidance
WACV 2024
A Probabilistic Framework for Modular Continual Learning
ICLR 2024
Compositional Foundation Models for Hierarchical Planning
NIPS 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
NIPS 2023
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
NIPS 2023
Post-processing Private Synthetic Data for Improving Utility on Selected Measures
NIPS 2023
Analyzing Generalization of Neural Networks through Loss Path Kernels
NIPS 2023
Towards robust and generalizable representations of extracellular data using contrastive learning
NIPS 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries
ICML 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
NIPS 2023
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
ICLR 2022
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
NIPS 2021
Targeted Neural Dynamical Modeling
NIPS 2021
Generative Ratio Matching Networks
ICLR 2020
Variational Russian Roulette for Deep Bayesian Nonparametrics
ICML 2019
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
NIPS 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
ICML 2018
HOUDINI: Lifelong Learning as Program Synthesis
NIPS 2018
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
NIPS 2017