Robin Walters
@RobinSFWalters
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Asst. Prof. at Khoury College of CS at Northeastern
Boston, MA
Joined February 2020
RT @ZhaoHaibo47588: Excited to share our #ICML2025 paper, Hierarchical Equivariant Policy via Frame Transfer. Our Frame Transfer interface….
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RT @bostonsymmetry: Registration is now open for Boston Symmetry Day on March 31! Sign up by March 21st at We have….
docs.google.com
Location: Alumni Center at Northeastern University, 716 Columbus Ave, Boston, MA 02120 Time: Monday, March 31, 2025, 9 AM - 5 PM Thank you for your interest in Boston Symmetry Day! Please fill out...
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RT @bostonsymmetry: Save the date -- Boston Symmetry Day 2025 will be held on March 31st, at Northeastern University! . Speakers and sponso….
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RT @BoZhao__: What can we learn from neural network model weights?. Join us for the Weight Space Learning Workshop at #ICLR2025! @iclr_conf….
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RT @Dian_Wang_: Honored to receive my first best paper nomination from @corl_conf! Had such a great time at #CoRL2024, huge thanks to the o….
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RT @HaojieHuang13: Generate the goal state and then infer the manipulation pick-place action. Feel free to check poster session 4 at #36 fo….
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RT @HelpingHandsLab: #CoRL2024 IMAGINATION POLICY: Using Generative Point Cloud Models for Learning Manipulation Policies Led by @HaojieHua….
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RT @Dian_Wang_: #CoRL2024 Looking forward to presenting Equivariant Diffusion Policy at Oral Session 1 on Nov 6 and Poster Session 2 on Nov….
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RT @EChatzipantazis: Join us on Monday October. 14th at 2pm (UTC+4) in #IROS2024 Workshop on Equivariant Robotics. A great lineup of keyno….
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RT @Dian_Wang_: Introducing Equivariant Diffusion Policy, a novel sample efficient BC algorithm based on equivariant diffusion. Our method….
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It's interesting that the much higher dimensional problem of point cloud generation leads to be better performance in the low dimensional problem of finding the best SE(3) pose. It might be point clouds have more geometric structure or another victory for overparameterization.
Excited to publish our recent work - Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation Policies!. It generated the imagination of the key-frame actions and achieved very high sample efficiency. Project Website:
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RT @HaojieHuang13: Excited to publish our recent work - Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation P….
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The reviewing quality was exceptional. Thank you to our fantastic reviewers!.
@GRaM_workshop decisions are out now! Woohoo! 🎉🎉 What a delight it was to read your 🌟brilliant papers 🌟! .We are thrilled to announce that we now have some great accepted extended abstracts and wonderful full papers accepted in the proceedings track to be published in PMLR.
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RT @maurice_weiler: Convolutional neural nets going to spacetime 🚀.Our new ICML24 paper shows how to build Lorentz-equivariant CNNs/MPNNs f….
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RT @SharvVadgama: 📣 This year at #ICML2024 we are hosting ✨ @GRaM_workshop ✨ Geometry-grounded representation learning and generative model….
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RT @HaojieHuang13: #ICLR24.We proposed FourTran, a very sample-efficient 3D manipulation pick-place model. 1. It can learn a nontrivial 3….
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A lot of work on symmetry in deep learning is focused on symmetry in data (e.g. equivariant neural networks), but there's lots of symmetry in parameter space too! You can use this structure to improve optimization algorithm speed and even generalization.
Excited to share our latest paper on symmetries in neural network parameters! #ICLR2024. Oral: Wed 10:00am, Halle A 2.Poster: Wed 10:45am-12:45pm, Halle B #206. Disappointed that I can’t join in person due to visa issues, but thrilled that @RobinSFWalters will represent our work!
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RT @GRaM_workshop: 📢#GRaM template for proceedings track is up on our website . Submit your great ideas in a #ICML….
gram-workshop.github.io
Geometry-grounded Representation Learning and Generative Modeling
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